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-\multicolumn{3}{>{\columncolor[rgb]{0.95,0.95,0.75}}c}{Here all of the terminal symbols receive non-terminal labels. The English words are in Urdu order.}\\ -\includegraphics[width=.45\linewidth]{SCFGs/urdu-step0} & & -\includegraphics[width=.45\linewidth]{SCFGs/english-step0} \\ \hline -\multicolumn{3}{>{\columncolor[rgb]{0.95,0.95,0.75}}c}{The PP rule reorders the Urdu postpositional phrase to be a prepositional phrase on the English side.}\\\includegraphics[width=.45\linewidth]{SCFGs/urdu-step1} & & -\includegraphics[width=.45\linewidth]{SCFGs/english-step1} \\ \hline\multicolumn{3}{>{\columncolor[rgb]{0.95,0.95,0.75}}c}{The English auxiliary verb and main verb get reordered with the application of the VP rule.}\\ -\includegraphics[width=.45\linewidth]{SCFGs/urdu-step2} & & -\includegraphics[width=.45\linewidth]{SCFGs/english-step2} \\ \hline -\multicolumn{3}{>{\columncolor[rgb]{0.95,0.95,0.75}}c}{This VP rule moves the English verb from the Urdu verb-final position to its correct place before the PP.}\\ -\includegraphics[width=.45\linewidth]{SCFGs/urdu-step3} & & \includegraphics[width=.45\linewidth]{SCFGs/english-step3} \\ \hline -\multicolumn{3}{>{\columncolor[rgb]{0.95,0.95,0.75}}c}{Applying the S rule, means that we have a complete translation of the Urdu sentence.}\\ -\includegraphics[width=.45\linewidth]{SCFGs/urdu-step4} & & \includegraphics[width=.45\linewidth]{SCFGs/english-step4} -\end{tabular} -\caption{Using SCFGs as the underlying formalism means that the process of translation is one of parsing. This shows how an English sentence can be generated by parsing the Urdu sentence using the rules given in Figure \ref{toy-scfg}}\label{toy-scfg-parse} -\end{figure} - - - -The translation models used in this workshop are synchronous context free grammars (SCFGs). -SCFGs \cite{lewis68scfg} generalize context free grammars so they generate pairs of related strings. -Because they generate pairs of strings they are useful for specifying the relationship between two languages, and can be used to describe translation and re-ordering. -Probabilistic SCFGs can be formally defined as follows: -\begin{itemize} -\item T$_{S}$: a set of source-language terminal symbols -\item T$_{T}$: a set of target-language terminal symbols -\item N: a shared set of nonterminal symbols -\item A set of rules of the form $\text{X} \rightarrow \langle \gamma, \alpha, \sim, w \rangle$ - \begin{itemize} - \item X $\in$ N - \item $\gamma$ is a sequence source terminals and non-terminals - \item $\alpha$ is a sequence of target terminals and non-terminals - \item $\sim$ is a one-to-one correspondence between the non-terminals in $\gamma$ and $\alpha$ - \item $w$ is a weight or probability assigned to the rule - \end{itemize} -\end{itemize} - - - -A toy example of an SCFG is given in Figure \ref{toy-scfg}. The nonterminal symbols, which are written in uppercase, are identical across the two right hand sides of the context free grammar rules, but can come in different orders. -The process of translation is accomplished by parsing the source language input sentence and simultaneously generating the target language output sentence. This -process is illustrated in Figure \ref{toy-scfg-parse}, which shows how parsing an Urdu sentence generates an English translation using the toy example grammar. The toy grammar and example parse omit the $w$ weights/probabilities assigned to the grammar rules. In practice there are a huge number of alternative translations and derivations, and assigning probabilities allows us to choose the best translation according to the model, and to reduce the search space by expanding only the most promising partial translations. - -SCFGs used for machine translation vary based on the set of non-terminal symbols that they use. -We briefly review two styles of SCFG: Hiero, an unsupervised approach which uses only a single non-terminal symbol, and SAMT or syntax-augmented MT, a fully-supervised approach that has a rich set of linguistically-motivated non-terminals, but which relies on a treebank-trained parser. -Our approach tries to combine the best aspects of these two approaches, by inducing a rich set of non-terminals in an unsupervised fashion. - -\section{Hiero: SCFGs with one non-terminal symbol}\label{sec:hiero} - -The use of SCFGs for statistical machine translation was popularized by \citet{Chiang2005} with the introduction of the Hiero system. Chiang's Hiero system extended the standard phrase-based approaches to statistical machine translation by allowing phrases that contain gaps. Chiang described how these {\it hierarchical phrases} could be obtained by straightforwardly extending the standard methods \cite{Koehn2004,Koehn2003,Tillmann2003,Venugopal2003} for extracting phrase pairs from word-aligned sentence pairs. Figure \ref{hiero-phrase-extraction} shows how a hierarchical phrase can be constructed by replacing two smaller phrase pairs with the nonterminals indexed $1$ and $2$. These rules are written in the same format as the SCFG rules given in Figure \ref{toy-scfg}. Although the Hiero rules are devoid of linguistic information, they are able to indicate reordering, as shown with the swapped positions of $X_1$ and $X_2$. - -\begin{figure} -\begin{center} -\includegraphics[width=.9\linewidth]{SCFGs/hiero-phrase-extraction.pdf} -\end{center} -\caption{An example of a hierarchal phrase extracted from a word-aligned Chinese-English sentence pair. Chiang's Hiero system used rules that were written in the form of synchronous grammars, but which are devoid of linguistic information.}\label{hiero-phrase-extraction} -\end{figure} - - -Rather than using the full power of the SCFG formalism, the Hiero system instead uses a simple grammar with one non-terminal symbol, X, to extend conventional phrase-based models to allow phrases with gaps in them. The Hiero system is technically a grammar-based approach to translation, but does not incorporate any linguistic information in its grammars. Its process of decoding is also one of parsing, and it employs the Cocke-Kasami-Younger (CKY) dynamic programming algorithm to find the best derivation using its probabilistic grammar rules. However, because Hiero grammars are devoid of linguistic information, they often fail to capture useful linguistic facts like that Urdu is post-positional and verb final. - -\section{SCFGs with syntactic labels extracted from supervised parses}\label{sec:samt} - - -\begin{figure} -\begin{center} -\includegraphics[height=3in]{SCFGs/scfg-phrase-extraction.pdf} -\end{center} -\caption{An example of extracting linguistically-motivated SCFGs by labeling phrase pairs using the labels of the corresponding nodes in a parse tree. Rules with syntactic non-terminals on the right-hand sides can be formed by replacing phrase pairs with their non-terminal labels, as shown with the VP on the right hand sides of the second NP rule.}\label{scfg-phrase-extraction} -\end{figure} - - -SCFGs with a rich set of linguistically motivated non-terminal symbols have been proposed as an alternative to Hiero. A number of approaches have been proposed for extracting linguistically-motivated grammars from a parsed parallel corpus \cite{Galley2004,samt}. These approaches extract SCFGs from a parallel corpus that has been parsed using a supervised parser that was trained on a treebank \cite{Marcus1993,Collins1996,Charniak1997}. -% -Figure \ref{scfg-phrase-extraction} shows how linguistically motivated grammar rules can be extracted from a training sentence pair that has been automatically parsed and word-aligned. Instead of assigning the generic label ``X'' to all extracted phrase pairs, as the Hiero model does, linguistic labels are extracted from the parse tree. - -In the standard phrase-based and hierarchical phrase-based approaches to machine translation, many of the ``phrases'' that are used are not phrases in the sense of syntactic constituents. They are simply sequences of words. For example, in Figure \ref{scfg-phrase-extraction}, the phrases {\it Australia is} and {\it one of} are examples of phrases which have consistent Chinese phrase pairs, but which do not correspond to nodes in the parse tree. If we were to limit ourselves to extracting only phrase pairs that were licensed by the parse tree and which had consistent word alignments, then we would have reduced coverage compared to Hiero. SAMT \cite{samt} achieves the same coverage as Hiero by generating complex labels for non-constituent phrases. - - -\begin{figure} -\begin{center} -\includegraphics[height=3in]{SCFGs/scfg-ccg-phrase-extraction.pdf} -\end{center} -\caption{An example of a CCG-style label for the non-constituent phrase {\it Australia is}. The label indicates that the non-constituent phrase would be an S if an NP were found to its right. This complex label can be treated like any other label during parsing and translation. }\label{scfg-ccg-phrase-extraction} -\end{figure} - - -SAMT grammars include traditional nonterminal categories taken directly from the monolingual parse trees (e.g. DT, NP, VP), and extended categories formed by gluing together adjacent nonterminals (e.g. NP+V, RB+JJ) and incomplete constituents that denote a category missing a child component to the left (e.g. NP\textbackslash DT) or to the right (e.g. NP/NN) in the style of Combinatory Categorial Grammars \cite{ccg1982}. SAMT grammars may also include hierarchical rules and glue rules \cite{chiang:2007} that are not linguistically motivated; such rules allow partial translations to be combined (with some penalty) without regard to syntactic structure. - -Last year's SCALE summer workshop \cite{SCALE-report} illustrated that SAMT could result significant improvements over the Hiero baseline for Urdu-English translation. - - -\section{Our approach: enriching SCFGs labels in an unsupervised fashion}\label{sec:our-approach} - -One of the major disadvantages of extracting SAMT-style SCFGs is that the parallel corpus needs to be parsed using a supervised parser that has been trained on treebank. The methods explored in this summer workshop obviate the need for a supervised parser, and instead automatically induce the grammars from unlabeled texts. The potential advantages of our approach are: -\begin{enumerate} -\item It can be applied to language pairs for which treebanks do not exist. -\item The set of non-terminal symbols is not tied to a particular treebank formalism, and therefore may be more appropriate for translation. -\end{enumerate} -In our experimental setup (described in detail in the next chapter), we begin with the set of phrase-pairs extracted by Hiero and posit a refined set of non-terminal labels for them. Like SAMT, our SCFGs have identical coverage to Hiero but with a richer set of labels. Unlike SAMT, our grammars are induced in an unsupervised fashion that does not require a parser, which makes our method applicable to any language pair, and arguably closer to statistical machine translation language-independent roots. - diff --git a/report/SCFGs/english-step0.pdf b/report/SCFGs/english-step0.pdf deleted file mode 100644 index e8964fba..00000000 Binary files a/report/SCFGs/english-step0.pdf and /dev/null differ diff --git a/report/SCFGs/english-step1.pdf b/report/SCFGs/english-step1.pdf deleted file mode 100644 index 29f56f1b..00000000 Binary files a/report/SCFGs/english-step1.pdf and /dev/null differ diff --git a/report/SCFGs/english-step2.pdf b/report/SCFGs/english-step2.pdf deleted file mode 100644 index 4afb06b7..00000000 Binary files a/report/SCFGs/english-step2.pdf and /dev/null differ diff --git a/report/SCFGs/english-step3.pdf b/report/SCFGs/english-step3.pdf deleted file mode 100644 index 1926b4dd..00000000 Binary files a/report/SCFGs/english-step3.pdf and /dev/null differ diff --git a/report/SCFGs/english-step4.pdf b/report/SCFGs/english-step4.pdf deleted file mode 100644 index ccc13807..00000000 Binary files a/report/SCFGs/english-step4.pdf and /dev/null differ diff --git a/report/SCFGs/example-scfg.pdf b/report/SCFGs/example-scfg.pdf deleted file mode 100644 index bc7e411e..00000000 Binary files a/report/SCFGs/example-scfg.pdf and /dev/null differ diff --git a/report/SCFGs/hiero-phrase-extraction.pdf b/report/SCFGs/hiero-phrase-extraction.pdf deleted file mode 100644 index 6e17218d..00000000 Binary files a/report/SCFGs/hiero-phrase-extraction.pdf and /dev/null differ diff --git a/report/SCFGs/hiero-tree.pdf b/report/SCFGs/hiero-tree.pdf deleted file mode 100644 index dc53e837..00000000 Binary files a/report/SCFGs/hiero-tree.pdf and /dev/null differ diff --git a/report/SCFGs/samt-tree.pdf b/report/SCFGs/samt-tree.pdf deleted file mode 100644 index 57cdec06..00000000 Binary files a/report/SCFGs/samt-tree.pdf and /dev/null differ diff --git a/report/SCFGs/scfg-ccg-phrase-extraction.pdf b/report/SCFGs/scfg-ccg-phrase-extraction.pdf deleted file mode 100644 index cc2cc5f0..00000000 Binary files a/report/SCFGs/scfg-ccg-phrase-extraction.pdf and /dev/null differ diff --git a/report/SCFGs/scfg-phrase-extraction.pdf b/report/SCFGs/scfg-phrase-extraction.pdf deleted file mode 100644 index 29263b9c..00000000 Binary files a/report/SCFGs/scfg-phrase-extraction.pdf and /dev/null differ diff --git a/report/SCFGs/urdu-input.pdf b/report/SCFGs/urdu-input.pdf deleted file mode 100644 index a367dbb8..00000000 Binary files a/report/SCFGs/urdu-input.pdf and /dev/null differ diff --git a/report/SCFGs/urdu-step0.pdf b/report/SCFGs/urdu-step0.pdf deleted file mode 100644 index 31a225b9..00000000 Binary files a/report/SCFGs/urdu-step0.pdf and /dev/null differ diff --git a/report/SCFGs/urdu-step1.pdf b/report/SCFGs/urdu-step1.pdf deleted file mode 100644 index 5d386332..00000000 Binary files a/report/SCFGs/urdu-step1.pdf and /dev/null differ diff --git a/report/SCFGs/urdu-step2.pdf b/report/SCFGs/urdu-step2.pdf deleted file mode 100644 index 13cd73dc..00000000 Binary files a/report/SCFGs/urdu-step2.pdf and /dev/null differ diff --git a/report/SCFGs/urdu-step3.pdf b/report/SCFGs/urdu-step3.pdf deleted file mode 100644 index 15636844..00000000 Binary files a/report/SCFGs/urdu-step3.pdf and /dev/null differ diff --git a/report/SCFGs/urdu-step4.pdf b/report/SCFGs/urdu-step4.pdf deleted file mode 100644 index 6a5fa2a7..00000000 Binary files a/report/SCFGs/urdu-step4.pdf and /dev/null differ diff --git a/report/align.pdf b/report/align.pdf deleted file mode 100644 index fd9a9965..00000000 Binary files a/report/align.pdf and /dev/null differ diff --git a/report/backoff/backoff.tex b/report/backoff/backoff.tex deleted file mode 100644 index a47e6296..00000000 --- a/report/backoff/backoff.tex +++ /dev/null @@ -1,76 +0,0 @@ -\begin{document} -\maketitle -%\chapter{Backoff Grammar} - -\section{Backoff Grammar} - -Multi-category grammars can better represent complex structure and reordering useful in machine translation, but their power is limited by the sparsity of the training data. Complex structures with limited representation in the grammar may not exist with sufficient contexts in the training data to be used to their fullest extent. This is likely to cause problems when translating structurally divergent language pairs. - -This portion of the project seeks to design a backoff grammar which can build on a multi-category grammar such as the one induced by the Pitman-Yor process described elsewhere in these proceedings. The backoff grammar adds the flexibility of a single category grammar without sacrificing reordering. - -\subsection{Naive Backoff} - -As was previously mentioned, given the sparsity of the training data, no phrase will have all of its linguistically possible contexts accounted for in the grammar. As an example, consider the production in (\ref{eq:whenwill}): - -\begin{equation}\label{eq:whenwill} -X \rightarrow \text{when will }Y\text{ be }Z -\end{equation} - -In English, this is a useful construction, and it is made more useful in translating Chinese, where it necessitates reordering to derive the most accurate translation. However, this is only possible so long as the necessary phrases exist in categories Y and Z. In the example thus far given, the English sentence ``when will they be ready" was possible with the rest of the grammar: ``they" existed as a possible production of Y, and ``ready" as a possible production of Z. Some phrases, however, may not exist, despite the fact that they might well produce a more appropriate translation. Suppose instead of ``they", one wanted to produce ``the pancakes" from Y, to create the valid sentence ``when will the pancakes be ready". If Y does not have such a production, the derivation must be broken down into smaller chunks combined with glue rules, which may not have the reordering power of (\ref{eq:whenwill}). - -This intuition can be applied to other instances, which will undoubtedly occur due to sparsity. An induced grammar may cover many useful constructions, but in order for those constructions to be put to best use in a SCFG derivation, non-terminals should not be restricted to only those in the pre-existing induced grammar. The most useful backoff grammar for translation would allow a rule to produce any other category (as is the case in a single category Hiero grammar), but prefer those constructions made most likely by the training data. - -In this formulation of the backoff grammar, additional rules were produced based on the induced multi-category grammar. The set of non-terminals $T$ was doubled, such that for each non-terminal $X_k \in T$, a corresponding nonterminal $X-backoff_k$ was produced. Each rule in the grammar was rewritten, replacing each $X_k$ on the RHS of the production with $X-backoff_k$. Backoff rules were added for each $X-backoff_k$ with a possible RHS of any of the original non-terminals. Backoff rules were assigned the feature BackoffRule, assigned 0 if $X-backoff_k$ had the RHS $X_k$ and 1 if $X-backoff_k$ had the RHS $X_j$ where $j \not = k$. - -\begin{figure} -\label{fig:naivebo} -\includegraphics{naivebackoff.jpg} -\caption{A sample derivation using a multi-category grammar augmented with the naive version of the backoff grammar. -\end{figure} - -Figure (\ref{fig:naivebo}) shows an example tree derived from an induced grammar which shows the behaviour of the backoff rules in a derivation. Notice that X8-bo, replacing X8 in the original X0 production, produced an X20 and an X1 in this derivation, while X16-bo produced an X16 as expected. - -This approach allowed derivations to utilize complex constructions like that in (\ref{eq:whenwill}), while still smoothing the output to allow alternate derivations of subconstituents. The multi-category grammar can behave like a single-category grammar when it is more useful, with a penalty. - -\subsection{Hierarchical Backoff} - -The next iteration of the backoff grammar built on the naive backoff grammar, encoding a hierarchy of backoff rules. The naive formulation of the grammar did not distinguish between the other categories except by the presence of other features. Ideally, a backoff grammar would preferentially allow similar non-terminals to backoff to the same backoff category. - -The hierarchical backoff process was another augmentation of the grammar, this time increasing the rules by creating sets of rules at different levels of the hierarchy. A strict rule hierarchy, making certain non-terminals strictly more general than a set of other non-terminals, was not absolutely necessary. Instead, this backoff process built the hierarchy based on the pre-existing grammar induction process, and determined category similarity based on the frequency of category assignment to phrases in the training data. - -This rough hierarchy came from inducing some set $G$ of multi-category grammars, varying the level of granularity to $$ where $n=|G|$. A complete grammar consisted of the complete rulesets from each grammar in $G$, augmented with backoff rules. - -For every grammar with number of categories $x_i | 1 \leq i < n$, a set of rules was added from each non-terminal $t_i$ in the $X_i$ grammar to each non-terminal $t_{i+1}$ in the $X_{i+1}$ grammar. These rules were each assigned the BackoffRule feature, with feature weight as in (\ref{eq:ftrwgt}), based on the frequency of phrases $p$ which were assigned both categories. - -\begin{equation} -\label{eq:ftrwgt} -BR = \log_2{P(t_{i+1} | t_i) \\ -P(t_{i+1} | t_i) = \frac{count( \{p\text{ assigned category }t_i\} \cap \{p\text{ assigned category }t_{i+1}\} )}{count( \{p \text{ assigned category }t_i)} -\end{equation} - -The addition of these rules allowed backoff categories to be preferentially chosen which bore similarity to the category originally specified by the induced rule. - -Though this hierarchy building process clearly does not create a true hierarchy, it also does not produce several unrelated levels of granularity. As seen in (\ref{fig:entropy}), rougher categories bore a strong relation to several of the finer categories. - -\begin{figure} -\label{fig:entropy} -\caption{Cross-entropy for the PYP-induced grammars.} -\includegraphics{hier-backoff.images/15-10.jpg} -\includegraphics{hier-backoff.images/30-105.jpg} -\end{figure} - -\subsection{Results} - -The backoff grammars were tested on BTEC and Urdu-English, using BLEU. The naive backoff grammar did not have a strong effect on the results, causing a reduced BLEU score. The hierarchical backoff grammar outperformed the baseline on both corpora, producing results very near to those of the CMU syntax-augmented machine translation system (SAMT). The hierarchical backoff method improved BLEU by +.88 in the case of BTEC, and +1.08 for Urdu-English. - -\begin{figure} -\label{fig:btec} -\includegraphics{btec.png} -\end{figure} - -\begin{figure} -\label{fig:urdu} -\includegraphics{urdu.png} -\end{figure} - -\end{document} \ No newline at end of file diff --git a/report/backoff/btec.png b/report/backoff/btec.png deleted file mode 100644 index ce5c10eb..00000000 Binary files a/report/backoff/btec.png and /dev/null differ diff --git a/report/backoff/naivebackoff.png b/report/backoff/naivebackoff.png deleted file mode 100644 index 7d141f54..00000000 Binary files a/report/backoff/naivebackoff.png and /dev/null differ diff --git a/report/backoff/urdu.png b/report/backoff/urdu.png deleted file mode 100644 index 2d3ae2a8..00000000 Binary files a/report/backoff/urdu.png and /dev/null differ diff --git a/report/biblio.bib b/report/biblio.bib deleted file mode 100644 index d2e8249a..00000000 --- a/report/biblio.bib +++ /dev/null @@ -1,670 +0,0 @@ -@inproceedings{blunsom:acl2009, - author = {Blunsom, Phil and Cohn, Trevor and Dyer, Chris and Osborne, Miles}, - title = {A {Gibbs} sampler for phrasal synchronous grammar induction}, - booktitle = {ACL-IJCNLP '09: Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2}, - year = {2009}, - pages = {782--790}, - location = {Suntec, Singapore}, - } - -@InProceedings{zhang:2008, - author = {Zhang, Hao and Quirk, Chris and Moore, Robert C. and Gildea, Daniel}, - title = {{Bayesian} Learning of Non-Compositional Phrases with Synchronous Parsing}, - booktitle = {Proceedings of ACL-08: HLT}, - month = {June}, - year = {2008}, - address = {Columbus, Ohio}, - pages = {97--105}, -} - -@inproceedings{blunsom:nips2008, - author = {Phil Blunsom and - Trevor Cohn and - Miles Osborne}, - title = {Bayesian Synchronous Grammar Induction}, - booktitle = {Advances in Neural Information Processing Systems 21, Proceedings of the Twenty-Second Annual Conference on Neural Information Processing Systems}, - pages = {161--168}, - editor = {Daphne Koller and - Dale Schuurmans and - Yoshua Bengio and - L{\'e}on Bottou}, - publisher = {MIT Press}, - year = {2009}, -} - - -@string{acl-1989 = {27th Annual Meeting of the Association for Computational Linguistics (ACL-1989)}} - -@string{acl-1989-address = {Vancouver, British Columbia, Canada}} - -@string{acl-1995 = {33rd Annual Meeting of the Association for Computational Linguistics (ACL-1995)}} - -@string{acl-1995-address = {Cambridge, Massachusetts}} - -@string{acl-1996 = {34rd Annual Meeting of the Association for Computational Linguistics (ACL-1996)}} - -@string{acl-1996-address = {Santa Cruz, California}} - -@string{acl-1997 = {35th Annual Meeting of the Association for Computational Linguistics (ACL-1997)}} - -@string{acl-1997-address = {Madrid, Spain}} - -@string{acl-1998 = {36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics (ACL-CoLing-1998)}} - -@string{acl-1998-address = {Montreal, Canada}} - -@string{acl-1999 = {Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics (ACL)}} - -@string{acl-1999-address = {College Park, Maryland}} - -@string{acl-2000 = {Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics (ACL-2000)}} - -@string{acl-2000-address = {Hong Kong}} - -@string{acl-2001 = {Proceedings of the 39th Annual Meeting of the Association for Computational Linguistics (ACL-2001)}} - -@string{acl-2001-address = {Toulouse, France}} - -@string{acl-2002 = {Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics (ACL-2002)}} - -@string{acl-2002-address = {Philadelphia, Pennsylvania}} - -@string{acl-2003 = {Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics (ACL-2003)}} - -@string{acl-2003-address = {Sapporo, Japan}} - -@string{acl-2004 = {Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL-2004)}} - -@string{acl-2004-address = {Barcelona, Spain}} - -@string{acl-2005 = {Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL-2005)}} - -@string{acl-2005-address = {Ann Arbor, Michigan}} - -@string{acl-2006 = {Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics (ACL-CoLing-2006)}} - -@string{acl-2006-address = {Sydney, Australia}} - -@string{acl-2007 = {Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL-2007)}} - -@string{acl-2007-address = {Prague, Czech Republic}} - -@string{acl-2008 = {Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies}} - -@string{acl-2008-address = {Colmbus, Ohio}} - -@string{acl-2009-address = {Singapore}} - -@string{amta-2002 = {Proceedings of the 5th Biennial Conference of the Association for Machine Translation in the Americas (AMTA-2002)}} - -@string{amta-2002-address = {Tiburon, California}} - -@string{amta-2004 = {Proceedings of the 6th Biennial Conference of the Association for Machine Translation in the Americas (AMTA-2004)}} - -@string{amta-2004-address = {Washington DC}} - -@string{amta-2006 = {Proceedings of the 7th Biennial Conference of the Association for Machine Translation in the Americas (AMTA-2006)}} - -@string{amta-2006-address = {Cambridge, Massachusetts}} - -@string{amta-2008 = {Proceedings of the 8th Biennial Conference of the Association for Machine Translation in the Americas (AMTA-2008)}} - -@string{amta-2008-address = {Honolulu, Hawaii}} - -@string{coling-2008 = {Proceedings of the 22nd International Conference on Computational Linguistics (COLING-2008)}} - -@string{coling-2008-address = {Manchester, England}} - -@string{eacl-1989 = {4th Conference of the European Chapter of the Association for Computational Linguistics (EACL-1989)}} - -@string{eacl-1989-address = {Manchester, England}} - -@string{eacl-2003 = {10th Conference of the European Chapter of the Association for Computational Linguistics (EACL-2003)}} - -@string{eacl-2003-address = {Budapest, Hungary}} - -@string{eacl-2006 = {11th Conference of the European Chapter of the Association for Computational Linguistics (EACL-2006)}} - -@string{eacl-2006-address = {Trento, Italy}} - -@string{eacl-2009 = {12th Conference of the European Chapter of the Association for Computational Linguistics (EACL-2009)}} - -@string{eacl-2009-address = {Athens, Greece}} - -@string{emnlp-2000 = {2000 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora}} - -@string{emnlp-2000-address = {Hong Kong}} - -@string{emnlp-2001 = {Proceedings of the 2001 Conference on Empirical Methods in Natural Language Processing (EMNLP-2001)}} - -@string{emnlp-2001-address = {Pittsburgh, Pennsylvania}} - -@string{emnlp-2002 = {Proceedings of the 2002 Conference on Empirical Methods in Natural Language Processing (EMNLP-2002)}} - -@string{emnlp-2002-address = {Philadelphia, Pennsylvania}} - -@string{emnlp-2003 = {Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing (EMNLP-2003)}} - -@string{emnlp-2003-address = {Sapporo, Japan}} - -@string{emnlp-2004 = {Proceedings of the 2004 Conference on Empirical Methods in Natural Language Processing (EMNLP-2004)}} - -@string{emnlp-2004-address = {Barcelona, Spain}} - -@string{emnlp-2005 = {Proceedings of the 2005 Conference on Empirical Methods in Natural Language Processing (EMNLP-2005)}} - -@string{emnlp-2005-address = {Vancouver, British Columbia., Canada}} - -@string{emnlp-2006 = {Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (EMNLP-2006)}} - -@string{emnlp-2006-address = {Sydney, Australia}} - -@string{emnlp-2007 = {Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL)}} - -@string{emnlp-2007-address = {Prague, Czech Republic}} - -@string{emnlp-2008 = {Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing (EMNLP-2008)}} - -@string{emnlp-2008-address = {Honolulu, Hawaii}} - -@string{emnlp-2009 = {Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing (EMNLP-2009)}} - -@string{emnlp-2009-address = {Singapore}} - -@string{hlt-2002 = {Proceedings of Second International Conference on Human Language Technology Research (HLT-02)}} - -@string{hlt-2002-address = {San Diego}} - -@string{hlt-naacl-2003 = {Proceedings of the Human Language Technology Conference of the North American chapter of the Association for Computational Linguistics (HLT/NAACL-2003)}} - -@string{hlt-naacl-2003-address = {Edmonton, Alberta}} - -@string{hlt-naacl-2004 = {Proceedings of the Human Language Technology Conference of the North American chapter of the Association for Computational Linguistics (HLT/NAACL-2004)}} - -@string{hlt-naacl-2004-address = {Boston, Massachusetts}} - -@string{hlt-naacl-2006 = {Proceedings of the Human Language Technology Conference of the North American chapter of the Association for Computational Linguistics (HLT/NAACL-2006)}} - 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Unfortunately, these improvements come at a cost: decoding with the induced grammars is more computationally expensive than decoding with the Hiero baseline grammars. Therefore, part of the workshop was devoted to research on efficient decoding techniques for induced grammars, the focus of this chapter. - -A simple example from our experimental setup illustrates the problem. On the Urdu-English task (\textsection\ref{sec:datasets}), the baseline Hiero grammar achieves a BLEU score of 20.8, while an induced 25-category grammar scores 21.7, a substantial improvement. However, using the same decoding algorithm, the Hiero grammar requires only 3.0 seconds to decode each sentence, while the 25-category grammar requires 52 seconds -- an order of magnitude slower. The prospects for decoding with grammars induced from larger data using more categories are even worse. - -Why is decoding so slow with these grammars? We first answer this question from a theoretical perspective (\textsection\ref{sec:overview}), and then measure the opportunity for improvement with the help of an oracle experiment (\textsection\ref{sec:oracle}). Finally we describe our contributions towards efficient decoding for these grammars, which include coarse-to-fine decoding (\textsection\ref{sec:ctf}) and grammar pruning techniques (\textsection\ref{sec:pruning}). - -\section{Decoding with Synchronous Context-free Grammars} \label{sec:overview} - -Informally, decoding with any synchronous context-free grammar is accomplished by first parsing the source sentence with the source projection of the grammar, and then reading off the string produced by the corresponding target parse. To illustrate this, suppose that we have the following grammar. -\begin{align*} - S &\rightarrow NP_1~VP_2 / NP_1~VP_2 \\ - NP &\rightarrow \textrm{ watashi wa } / \textrm{ I }\\ - NP &\rightarrow \textrm{ hako wo } / \textrm{ the box }\\ - VP &\rightarrow NP_1~V_2 / V_1~NP_2 \\ - V &\rightarrow \textrm{ akemasu } / \textrm{ open } -\end{align*} -We show a parse of the source sentence {\it watashi wa hako wo akemasu} under the source projection of this grammar below.\footnote{This example is borrowed from ???} -\begin{center} - \begin{tikzpicture}[edge from parent path= {(\tikzparentnode.south) -- (\tikzchildnode.north)}] - \node{S}[sibling distance=1in] - child {node {NP}[sibling distance=0.5in] - child {node {watashi}} - child {node {wa}}} - child {node {VP}[sibling distance=0.75in] - child {node {NP}[sibling distance=0.5in] - child {node {hako}} - child {node {wo}}} - child {node {V} - child {node {akemasu}}}}; - \end{tikzpicture} -\end{center} -This parse implies a corresponding unique target parse tree that is isomporphic to the source parse up to the ordering of child nonterminals and the identity and ordering of nonterminals, as illustrated below. All that is needed to obtain the translation is to read off the target nonterminal string at the leaves of the tree. -\begin{center} - \begin{tikzpicture}[edge from parent path= {(\tikzparentnode.south) -- (\tikzchildnode.north)}] - \node(S1a) at (0,0){S}[sibling distance=1in] - child {node(NP2a) {NP}[sibling distance=0.5in] - child {node {watashi}} - child {node {wa}}} - child {node(VP3a) {VP}[sibling distance=0.75in] - child {node (NP4a) {NP}[sibling distance=0.5in] - child {node {hako}} - child {node {wo}}} - child {node(V5a) {V} - child {node {akemasu}}}}; - \node (S1b) at (2.5in,0) {S}[sibling distance=1in] - child {node (NP2b) {NP}[sibling distance=0.5in] - child {node {I}}} - child {node (VP3b) {VP}[sibling distance=0.75in] - child {node (V5b) {V} - child {node {open}}} - child {node (NP4b) {NP}[sibling distance=0.5in] - child {node {the}} - child {node {box}}}}; - \draw[->,dotted] (S1a) -- (S1b); - \draw[->,dotted] (NP2a) ..controls +(1.25in,0.25in) .. (NP2b); - \draw[->,dotted] (VP3a) ..controls +(1.25in,-0.25in) .. (VP3b); - \draw[->,dotted] (NP4a) ..controls +(1.625in,0.25in) .. (NP4b); - \draw[->,dotted] (V5a) ..controls +(0.875in,-0.25in) .. (V5b); - \end{tikzpicture} -\end{center} -In general, however, there will be more than one parse of a given sentence -- indeed, there may be exponentially many parses. The set of all possible parses can can be computed efficiently using dynamic programming in the form of the CKY algorithm or its variants (we use CKY+). This produces a {\it hypergraph} (or {\it packed chart}) containing all parses, which requires at most $O(Gn^3)$ time to construct. The value $G$ is a grammar constant tied to properties of the grammar -- as a loose bound, it will be at least cubic in the size of the set of nonterminal symbols. Consequently, a key problem is that {\bf parsing time is strongly correlated with the number of nonterminal symbols in the grammar}. This is why parsing with 25 categories is an order of magnitude slower than parsing with two categories as in the baseline. - -Of course, parsing the source does not completely solve the translation problem, as in our translation models we need to consider the probability of each string under an $n$-gram language model. This intersection carries with it even worse computational overhead. A common approach to decoding with synchronous grammars is the {\it two-pass} strategy. -\begin{enumerate} - \item The source sentence is {\it exhaustively} parsed to produce a packed chart (called the {\it -LM hypergraph}). - \item This chart, itself a context-free grammar encoding all possible target sentences, is then intersected with an $n$-gram language model. The search space for this intersection is a much larger hypergraph (called the {\it +LM hypergraph}), constructed with heavy pruning to counteract complexity effects. -\end{enumerate} -Although some algorithms in the literature are only described implicitly in these terms, most of them follow this strategy \citep{Chiang2005,Huang+Chiang:2007:acl,venugopal-zollmann-stephan:2007:main,denero-EtAl:2009:NAACLHLT09,denero-pauls-klein:2009:Short,hopkins-langmead:2009:EMNLP,hopkins-langmead:2010:EMNLP,iglesias-EtAl:2009:NAACLHLT09}. The most popular of these, the {\it cube pruning} algorithm of \citet{Chiang2005}, is the baseline algorithm implemented in our decoder \citep{dyer-EtAl:2010:Demos}, making it a natural starting point for our exploration. The amount of work done in cube pruning is a constant multiplier times the size of the -LM hypergraph, so reducing its size is the key to producing faster two-pass algorithms. Therefore, we will consider approaches that construct a pruned -LM hypergraph. - -\section{Oracle Experiments}\label{sec:oracle} - -At the outset, we wondered what effect substituting a pruned -LM hypergraph for the full -LM hypergraph would have on translation accuracy. To measure this, we ran an oracle experiment. -\begin{enumerate} - \item Produce the complete -LM hypergraph. - \item Prune the -LM hypergraph using inside-outside pruning. - \item Integrate the language model on the pruned -LM hypergraph via cube pruning. -\end{enumerate} -The idea behind inside-outside pruning is simple: since we have access to the complete chart, we can calculate the ratio between the globally highest-scoring parse and the highest-scoring parse passing through any particular hyperedge. We prune the hyperedge if this ratio falls below some pruning threshold. By varying the threshold, we retain -LM hypergraphs of different sizes. - -An important point is that the -LM hypergraph incorporates only local features from the translation model and not the non-local language model feature. This has two consequences. First, it is possible to prune away the parse yielding the globally optimal translation under the combined model. Second, the ranking of parses under the translation model features is likely to be very poor. Nonetheless, it is important to recognize that the experiment is still idealized because it incorporates information from the full -LM hypergraph during pruning, and this information will not be available to us in practical methods that must avoid building the full -LM hypergraph altogether. - -The results of an initial oracle experiment are shown in Figure~\ref{figure:oracle-untuned}. These initial results are discouraging: we find that it is only possible to prune between twenty and thirty percent of the -LM hypergraph without incurring penalties in downstream BLEU score. - -\begin{figure} - \includegraphics[scale=0.5]{prune-untuned} - \caption{Oracle experiment: final BLEU score vs. percent of -LM forest retained after an initial inside-outside pruning pass. \label{figure:oracle-untuned}} -\end{figure} - -This initial result was disappointing, so we considered a different oracle approximation. In this case, we first tuned the local features using minimum error rate training, and used the subsequent set of feature weights for inside-outside pruning. This approximation turns out to produce a much better inside-outside pruning of the first-pass hypergraph. The results show (Figure~\ref{figure:oracle-tuned}) that it is possible to discard much more of this hypergraph before the second pass without harming overall accuracy -- possibly as much as three quarters of it. This result shows that heavy pruning of a -LM forest might be a means of improving decoding speed without harming translation accuracy. - -\begin{figure} - \includegraphics[scale=0.5]{prune-tuned} - \caption{Second oracle experiment: final BLEU score vs. percent of -LM forest retained after an initial inside-outside pruning pass using weights tuned for -LM decoding. \label{figure:oracle-untuned}} -\end{figure} - -\section{Coarse-to-Fine Decoding}\label{sec:ctf} - -Motivated by our oracle experiment, we implemented {\it coarse-to-fine parsing} to generate the -LM hypergraph. The idea behind the algorithm is simple: we first parse the source sentence using a projected grammar with a much lower grammar constant (the coarse grammar), which can be done very quickly. The resulting hypergraph is pruned using inside-outside, and we then parse the sentence again with the true grammar (the fine grammar), limiting the parse only to those edges whose projection appears in the pruned coarse hypergraph. If the original parse is sufficiently pruned, then this second pass will take much less time than an exhaustive parse with the same grammar. - -The first decision we need to make is how to obtain the coarse grammar. Many strategies are possible; for our experiments we chose to simply map all nonterminals to X. In essence, this means that we are decoding with the baseline Hiero grammar; although \citet{denero-EtAl:2009:NAACLHLT09} found that this simple strategy was ineffective for grammars estimated using parsers, the strategy makes intuitive sense for our induced grammars since they are generated by decorating Hiero grammars with finer-grained categories. As shown in Figure~\ref{fig:ctf}, we found that by varying the pruning parameter, we obtained different tradeoffs in speed and accuracy. Most encouraging, however, was the fact that we were able to lower decoding speed by nearly 40\% without any reduction in overall translation accuracy. - -An implementation detail that was important to our experiments was re-parsing. A subtle feature of coarse-to-fine parsing is that some coarse parses do not correspond to any parse in the fine grammar -- this is a consequence of the coarse grammar conflating two otherwise distinct nonterminal symbols. We discovered that a fairly common failure case for our parser occurred when all coarse parses corresponding to true fine parses were pruned away in the first pass. To work around this problem, whenever a fine parse was not found, we widened the beam and repruned the coarse hypergraph more conservatively. - -\section{Grammar Pruning}\label{sec:pruning} - -An alternative means of reducing the overhead of parsing is to prune the translation grammar. Although a pruned grammar will still retain the same number of nonterminal symbols, parsing time may be substantially improved if there are simply fewer rules in the grammar. Pruning the grammar might reasonably be viewed as a final step in grammar induction; however as the grammar induction methods explored in this workshop produced difficult to use grammars, we include this here as a means of working with them more efficiently. The pruning algorithm was fairly straightforward: we first clustered all rules that had the same source side, apart from differences in nonterminal symbols in either right-hand or left-hand side. We then sorted the rules in each cluster by $p(e|f)$, and retained only the top $n$ -rules. We then decoding the resulting grammars with no other algorithmic modifications. These results are presented in Table~\ref{tab:pruning}. - -\begin{table} - \begin{tabular}{rrrr} \hline - $n$ & memory & time (s) & BLEU \\ \hline \hline - 10 & 1.3G & 391.1 & 26.3\\ - 20 & 1.7G & 695.5 & 26.9\\ - 30 & 1.9G & 839.2 & 26.2\\ - 40 & 2.2G & 983.8 & 25.9\\ - 50 & 2.5G & 1048 & 26.4\\ - $\infty$ & 6.1G & 3399 & 27.0\\ \hline - \end{tabular} -\end{table} - -Though encouraging, the results here are somewhat mixed: we do not find that performance, as measured by BLEU, degrades monotonically with decoding time, although decoding time varies with $n$ nicely as expected. Indeed, the worst results on this dataset are roughly even with the baseline, meaning that we have sacrificed all of the increased accuracy of the grammar to obtain the speedup. Nevertheless, it may be that with slightly more sophisticated pruning techniques, we could obtain similar speedups without any corresponding loss in accuracy. - -\section{Discussion} - -The induced grammars studied in this workshop present serious challenges for decoding algorithms. However, the fairly simple techniques used here, and the resulting improvements in performance, demonstrate that efficient decoding with induced grammars is a reasonable goal. Using a very simple coarse-to-fine algorithm, we were able to reduce decoding time by nearly half. This is still far from being as efficient as decoding with a baseline grammar, but it is unrealistic to expect that a single technique will solve this kind of hard algorithmic problem. On the other hand, it is likely that the coarse-to-fine technique could be combined with other techniques to provide substantial speedups. An obvious experiment that is suggested by the current results is to do inside-outside pruning with the tuned -LM grammars used in our oracle experiment. That experiment suggested that using a simpler model tuned for the final task yielded more accurate pruning than using a subset of the full model for pruning. We intended to pursue this combination in further experiments. Several recent techniques from the literature that may prove useful \citep{denero-EtAl:2009:NAACLHLT09,denero-pauls-klein:2009:Short,hopkins-langmead:2009:EMNLP}. 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-\makeatletter - -\title{CLSP Workshop 2010: \\ Pre-Workshop Meeting} -\date{24 May, 2010} - -\begin{document} -\maketitle - -\centering -\subsection*{Attendees} -Phil Blunsom, Adam Lopez, Chris Dyer, Jonathen Graehl, Vladimir Eidelman, Ziyuan Wang, Olivia Buzek, Desai Chen. - -\subsection*{Apologies} -Trevor Cohn, Jan Botha. - -\section*{Agenda} -\begin{enumerate} -\centering -\item Opening welcome and introductions -\item Presentation: Workshop overview and goals -\item Undergraduate student mentoring -\item Preliminary graduate student goals -\item Draft workshop work plan -\item Pre-workshop tasks -\item JHU accounts and resources -\end{enumerate} - -\end{document} diff --git a/report/intro_slides/arabic-good.graffle b/report/intro_slides/arabic-good.graffle deleted file mode 100644 index 72ff7d78..00000000 --- a/report/intro_slides/arabic-good.graffle +++ /dev/null @@ -1,353 +0,0 @@ - - - - - ActiveLayerIndex - 0 - AutoAdjust - - CanvasColor - - w - 1 - - CanvasOrigin - {0, 0} - CanvasScale - 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-%% sloppy linebreaks -%\sloppy - -%% no extra spacing after dots -%\frenchspacing - -\makeatletter -\setlength{\columnsep}{3mm} % this one's nasty!!! - -%\setlength{\topmargin}{0in} -%\setlength{\headheight}{0in} -%\setlength{\headsep}{-0.2in} -%\setlength{\textheight}{10.0in} -%\setlength{\oddsidemargin}{0in} -%\setlength{\textwidth}{6.5in} -\setlength\titlebox{1.65in} -\renewcommand{\baselinestretch}{0.96} -\setlength{\textfloatsep}{3mm} -\setlength{\floatsep}{1.5mm} - - -\title{Unsupervised models of Synchronous Grammar Induction for SMT} -\author{ - Phil Blunsom\\ - %\vspace{6pt} - Phil.Blunsom@comlab.ox.ac.uk\\ -% {\rm $^*$Computing Laboratory}\\ - University of Oxford\\ - \And - Alex Clark\\ - %\vspace{6pt} - alexc@cs.rhul.ac.uk\\ -% {\rm $^\textrm{\textdagger}$Department of Computer Science}\\ - Royal Holloway University - \And - Trevor Cohn\\ - %\vspace{6pt} - T.Cohn@dcs.shef.ac.uk\\ -% {\rm $^\textrm{\textdagger}$Department of Computer Science}\\ - University of Shefield -\\ - \AND - Chris Dyer\\ - %\vspace{6pt} - redpony@umd.edu\\ -% {\rm $^\textrm{\textdagger}$Department of Computer Science}\\ - University of Maryland - \And - Adam Lopez\\ - %\vspace{6pt} - alopez@inf.ed.ac.uk\\ -% {\rm $^\textrm{\textdagger}$Department of Computer Science}\\ - University of Edinburgh -} - -\begin{document} -\maketitle - -\begin{abstract} -Synchronous grammar transducers have made a big impact in the field of machine translation in recent years. -However, current techniques for acquiring translation grammars are either overly simplistic or else too heavily reliant on the availability of high-quality statistical parsers. -We propose the development of algorithms for large-scale unsupervised synchronous grammar induction. -Using advanced clustering techniques from machine learning we aim to induce grammars which use a rich set of non-terminals, %, in contrast to many existing approaches which have only one. -thereby producing high quality translation models for language pairs solely using a parallel corpus. %, without relying on treebank parsers. -\end{abstract} - -%%Research into statistical machine translation has changed dramatically in recent years with the introduction of grammar-based transducers (e.g., Chang's Hiero and USC/ISI's syntax-based system). -%A critical component of synchronous grammar translation models is their \emph{grammar} which encodes translational equivalence and licenses reordering between tokens in the source and target languages. -%There is considerable scope for improving beyond current techniques for automatically acquiring synchronous grammars from bilingual corpora, which seek to find either extremely simple grammars with only one non-terminal or else rely on treebank-trained parsers. -%The simple grammars are incapable of representing constituency information, while the richer grammars limit the systems' portability to new target languages while enforcing a restrictive notion of linguistic constituency. -%Instead we propose to develop an unsupervised method for large-scale unsupervised synchronous grammar induction using multiple non-terminal symbols to represent contextual information. -%In such a way we can harness the benefits of a richer grammar without the limiting data requirements or linguistic constraints. - -The last decade of research in Statistical Machine Translation (SMT) has seen rapid progress. %with small scale research systems maturing into large commercial products and ubiquitous online tools. %\footnote{e.g., translate.google.com, www.systran.co.uk, www.languageweaver.com} -Unfortunately the success of SMT has not been uniform; -%current state-of-the-art translation output varies markedly in quality depending on the languages being translated. -%Those language pairs that are -closely related language pairs -%(e.g., English and French) -can be translated with a high degree of precision, while for distant pairs -%(e.g., English and Chinese) -the result is far from acceptable. -It is tempting to argue that SMT's current limitations can be overcome simply by increasing the amount of data on which the systems are trained. -However, large scale evaluation campaigns for Chinese~$\rightarrow$~English translation have not yielded the expected gains despite the increasing size of the models. -%While many researchers are tackling these issues, their proposed solutions are limited by focusing on more expressive models of translation rather than addressing the issue of how, and what, translation units are learnt a priori. - -Those models which have been most successful for translating between structurally divergent language pairs have been based on synchronous tree substitution grammars (STSG). -%However these successes have been tempered by a reliance on high quality monolingual parse trees on the output side of the translation model, severely restricting the applicability of such models to the case of translating into English. -A critical component of these translation models is their \emph{grammar} which encodes translational equivalence and licenses reordering between tokens in the source and target languages. -There is considerable scope for improving beyond current techniques for automatically acquiring synchronous grammars from bilingual corpora, which seek to find either extremely simple grammars with only one non-terminal or else rely on treebank-trained parsers. -The simple grammars are incapable of representing the substitutability of a constituent, while the richer grammars limit the systems' portability to new target languages while enforcing a restrictive notion of linguistic constituency (Figure \ref{fig:models}). -%A further, but more subtle, limitation of these models is the assumption that the particular brand of linguistic structure assigned by a parser (usually a form of phrase structure grammar learnt from the Penn. Treebank) is predominantly isomorphic to that of the input language; an assumption which is rarely true for distantly related language pairs (or even closely related ones: Figure \ref{fig:models}). - -Clearly there is a need for research into the unsupervised induction of synchronous grammar based translation models. -Previous research has focussed on structured learning approaches requiring costly global inference over translation pair derivations, limiting the ability of these models to be scaled to large datasets. -Here we propose the more pragmatic approach of embracing existing algorithms for inducing unlabelled SCFGs (e.g. the popular Hiero model) as a starting point, and then using state-of-the-art clustering and topic modelling algorithms to independently learn syntactic congruence classes for translation rules in the grammar. - -\begin{figure} - \subfigure[Formal syntax]{\includegraphics[scale=0.34]{JeNeVeuxPasTravailler-hiero.pdf}} - \subfigure[Linguistic syntax]{\includegraphics[scale=0.34]{JeNeVeuxPasTravailler-tsg.pdf}} -\caption{What is the best syntactic structure for SMT?} -\label{fig:models} -\end{figure} - -The agenda of the workshop will be motivated by two goals: (1) to investigate the role of constituency and syntactic congruence in synchronous grammars; (2) to develop scalable algorithms for assigning labels to translation rules in Hiero style grammars. These algorithms will be implemented within the Joshua decoder. - -\paragraph{1) Synchronous constituency} -The first goal deals with the question of the degree to which practical synchronous grammar SMT systems should be based on linguistic or non-linguistic models of syntax. -Previous work has assumed a linguistic motivation, but there is a compelling argument that a more appropriate representation may be one which specifically addresses the divergence between a given language pair (Figure~\ref{fig:models}). -Such a grammar might simply encode the number of tokens in the constituent being generated, the number of reordering operations on the path from the root to that constituent, or whether a constituent prefers to reorder in a specific direction. - -\paragraph{2) Clustering translation units} -The second goal will be to adapt existing unsupervised clustering techniques, such as Latent Dirichlet Allocation (LDA) and Hierarchical Dirichlet Processes (HDPs), to the task of assigning equivalence classes to phrase translations. -Inspired by work in monolingual PCFG learning, we will investigate generative models which describe the production of phrase translations in terms of sequences of tokens (or word classes) and their observed contexts. - -By investigating these goals in the context of a CLSP workshop we hope to both generate interest and further research into widely applicable unsupervised techniques for synchronous grammar induction, and to provide a benchmark implementation ready for wide adoption within the SMT research community. -\end{document} diff --git a/report/intro_slides/context_lda.pdf b/report/intro_slides/context_lda.pdf deleted file mode 100644 index 0537f704..00000000 Binary files a/report/intro_slides/context_lda.pdf and /dev/null differ diff --git a/report/intro_slides/deal.pdf b/report/intro_slides/deal.pdf deleted file mode 100644 index fd92787a..00000000 Binary files a/report/intro_slides/deal.pdf and /dev/null differ diff --git a/report/intro_slides/deal_first.pdf b/report/intro_slides/deal_first.pdf deleted file mode 100644 index 59049c22..00000000 Binary files a/report/intro_slides/deal_first.pdf and /dev/null differ diff --git a/report/intro_slides/deal_more.pdf b/report/intro_slides/deal_more.pdf deleted file mode 100644 index 434a011a..00000000 Binary files a/report/intro_slides/deal_more.pdf and /dev/null differ diff --git a/report/intro_slides/deal_numbers.pdf b/report/intro_slides/deal_numbers.pdf deleted file mode 100644 index c16af67d..00000000 Binary files a/report/intro_slides/deal_numbers.pdf and /dev/null differ diff --git a/report/intro_slides/desai.jpg b/report/intro_slides/desai.jpg deleted file mode 100644 index 1c64307f..00000000 Binary files a/report/intro_slides/desai.jpg and /dev/null differ diff --git a/report/intro_slides/dyer.jpg b/report/intro_slides/dyer.jpg deleted file mode 100644 index 382cf56c..00000000 Binary files a/report/intro_slides/dyer.jpg and /dev/null differ diff --git a/report/intro_slides/final_slides.pdf b/report/intro_slides/final_slides.pdf deleted file mode 100644 index cb842396..00000000 Binary files a/report/intro_slides/final_slides.pdf and /dev/null differ diff --git a/report/intro_slides/final_slides.tex b/report/intro_slides/final_slides.tex deleted file mode 100644 index a73481ac..00000000 --- a/report/intro_slides/final_slides.tex +++ /dev/null @@ -1,783 +0,0 @@ -\documentclass{beamer} - 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-% rules -\newcommand{\psr}[2]{#1 $\rightarrow \langle $ #2 $\rangle$} - -\newenvironment{unpacked_itemize}{ -\begin{itemize} - \setlength{\itemsep}{10pt} - \setlength{\parskip}{0pt} - \setlength{\parsep}{0pt} -}{\end{itemize}} - -\newcommand{\condon}{\hspace{0pt} | \hspace{1pt}} -\definecolor{darkblue}{rgb}{0,0,0.6} -\newcommand{\blueexample}[1]{\textcolor{darkblue}{\rm #1}} - -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -\newcommand{\ws}{\ensuremath{\vec{w}}} -\newcommand{\pu}{\ensuremath{P_0}} -\newcommand{\bx}{\mathbf{x}} -\newcommand{\bz}{\mathbf{z}} -\newcommand{\bd}{\mathbf{d}} -\newcommand{\by}{\mathbf{y}} -\newcommand\bleu{${B{\scriptstyle LEU}}$} - - -\title[Models of SCFG Induction]{Models of Synchronous Grammar Induction for SMT} - -\author[CLSP Workshop 2010]{ - Workshop 2010 - %Phil Blunsom$^1$ \and Trevor Cohn$^2$ \and Chris Dyer$^3$ \and Adam Lopez$^4$ -} - -\institute[Baltimore]{ - The Center for Speech and Language Processing \\ Johns Hopkins University -% $^1$University of Oxford\\ -% $^2$University of Sheffield\\ -% $^3$Carnegie Mellon University\\ -% $^4$University of Edinburgh -} -\date[June 28]{June 28, 2010} - -%\subject{Unsupervised models of Synchronous Grammar Induction for SMT} - -%\pgfdeclareimage[height=1.0cm]{university-logo}{logo} -%\logo{\pgfuseimage{university-logo}} - -%\AtBeginSection[] -%{ -% \begin{frame}{Outline} -% %\tableofcontents[currentsection,currentsubsection] -% \tableofcontents[currentsection] -% \end{frame} -%} - -%\beamerdefaultoverlayspecification{<+->} - -\begin{document} - -\begin{frame} - \titlepage -\end{frame} - -%\begin{frame}{Outline} -% \tableofcontents -% You might wish to add the option [pausesections] -%\end{frame} - -%\begin{frame}{Outline} -% \tableofcontents -% % You might wish to add the option [pausesections] -%\end{frame} - - -%\begin{frame}[t]{Team members} -%\begin{center} -%{\bf Senior Members} \\ -% Phil Blunsom (Oxford)\\ -% Trevor Cohn (Sheffield)\\ -% Adam Lopez (Edinburgh/COE)\\ -% Chris Dyer (CMU)\\ -% Jonathan Graehl (ISI)\\ -% Chris Callison-Burch (JHU)\\ -%\vspace{0.1in} -%{\bf Graduate Students} \\ -% Jan Botha (Oxford) \\ -% Vladimir Eidelman (Maryland) \\ -% Ziyuan Wang (JHU) \\ -% ThuyLinh Nguyen (CMU) \\ -%\vspace{0.1in} -%{\bf Undergraduate Students} \\ -% Olivia Buzek (Maryland) \\ -% Desai Chen (CMU) \\ -%\end{center} -%\end{frame} - - - -\begin{frame}[t]{Statistical machine translation} -%\vspace{1.0cm} -\begin{exampleblock}{Urdu $\rightarrow$ English} - \begin{figure} - {\centering \includegraphics[scale=0.55]{urdu.pdf}} - \end{figure} -\vspace{0.10cm} -\end{exampleblock} -\begin{itemize} - \item Statistical machine translation: Learn how to translate from parallel corpora. -\end{itemize} -\end{frame} - - -\begin{frame}[t]{Statistical machine translation: } -%\vspace{1.0cm} -\begin{exampleblock}{Urdu $\rightarrow$ English} - \begin{figure} - {\centering \includegraphics[scale=0.55]{urdu-ref.pdf}} - \end{figure} -\end{exampleblock} -\begin{itemize} - \item Statistical machine translation: Learn how to translate from parallel corpora -\end{itemize} -\end{frame} - -\begin{frame}[t]{Statistical machine translation: state-of-the-art} -%\vspace{1.0cm} -\begin{exampleblock}{Urdu $\rightarrow$ English} - \begin{figure} - {\centering \includegraphics[scale=0.55]{urdu-bl.pdf}} - \end{figure} -\end{exampleblock} -\begin{itemize} - \item Current state-of-the-art translation models struggle with language pairs which exhibit large differences in structure. -\end{itemize} -\end{frame} - -\begin{frame}[t]{Statistical machine translation: successes} -\begin{center} - \includegraphics[scale=0.35]{GoogleTranslateLanguages.pdf} -\end{center} -\end{frame} - -\begin{frame}[t]{Statistical machine translation: limitations} -\vspace{1.0cm} - \begin{table} - \centering - \begin{tabular}{|l|l|} - \hline - {\bf English} & {\bf \textcolor{blue}{Who wrote} \textcolor{red}{this letter}?} \\ - \hline - Arabic & \begin{Geeza}من الذي كتب هذه الرسالة؟\end{Geeza} \\ - & \textcolor{gray}{(function-word)} \textcolor{blue}{(who)} \textcolor{green}{(wrote)} \textcolor{red}{(this)} \textcolor{orange}{(the-letter)} \\ - \hline - Chinese & \begin{CJK}\textcolor{red}{è¿™å° ä¿¡} \textcolor{blue}{是 è° å†™} çš„ ？\end{CJK} \\ - & \textcolor{red}{(this) (letter)} \textcolor{blue}{(be) (who) (write) (come-from)} \textcolor{gray}{(function-word)} \\ - \hline - \end{tabular} - \end{table} -\end{frame} - - -\begin{frame}[t]{Statistical machine translation: limitations} -\vspace{1.0cm} -\begin{exampleblock}{Structural divergence between languages:} - %\vspace{0.3cm} - \begin{table} - \centering - \only<1>{ - \begin{tabular}{|l|l|} - \hline - {\bf English} & {\bf Who wrote this letter?} \\ - \hline - Arabic & \begin{Geeza}من الذي كتب هذه الرسالة؟\end{Geeza} \\ - & \textcolor{gray}{(function-word)} (who) (wrote) (this) (the-letter) \\ - \hline - Chinese & \begin{CJK}è¿™å° ä¿¡ 是 è° å†™ çš„ ？\end{CJK} \\ - & (this) (letter) (be) (who) (write) (come-from) \textcolor{gray}{(function-word)} \\ - \hline - \end{tabular} - } - \only<2>{ - \begin{tabular}{|l|l|} - \hline - {\bf English} & {\bf \textcolor{blue}{Who} \textcolor{green}{wrote} \textcolor{red}{this} \textcolor{orange}{letter?}} \\ - \hline - Arabic & \begin{Geeza}من الذي كتب هذه الرسالة؟\end{Geeza} \\ - & \textcolor{gray}{(function-word)} \textcolor{blue}{(who)} \textcolor{green}{(wrote)} \textcolor{red}{(this)} \textcolor{orange}{(the-letter)} \\ - \hline - Chinese & \begin{CJK}è¿™å° ä¿¡ 是 è° å†™ çš„ ？\end{CJK} \\ - & (this) (letter) (be) (who) (write) (come-from) \textcolor{gray}{(function-word)} \\ - \hline - \end{tabular} - } - \only<3->{ - \begin{tabular}{|l|l|} - \hline - {\bf English} & {\bf \textcolor{blue}{Who wrote} \textcolor{red}{this letter}?} \\ - \hline - Arabic & \begin{Geeza}من الذي كتب هذه الرسالة؟\end{Geeza} \\ - & \textcolor{gray}{(function-word)} (who) (wrote) (this) (the-letter) \\ - \hline - Chinese & \begin{CJK}\textcolor{red}{è¿™å° ä¿¡} \textcolor{blue}{是 è° å†™} çš„ ？\end{CJK} \\ - & \textcolor{red}{(this) (letter)} \textcolor{blue}{(be) (who) (write) (come-from)} \textcolor{gray}{(function-word)} \\ - \hline - \end{tabular} - } - \end{table} -\end{exampleblock} -\only<4>{ - \begin{itemize} - \item Phrasal translation equivalences - \item Constituent reordering - \item Morphology - \end{itemize} -} -\end{frame} - -\begin{frame} -\frametitle{Using syntax in Machine Translation:} - \footnotesize - \begin{block}{Synchronous Context Free Grammar (SCFG)} - \begin{figure} - \begin{align*} - \alert<2>{S} & \alert<2>{\rightarrow \langle X\ind{1},\ X\ind{1} \rangle} - &\quad \alert<3,5>{X} & \alert<3,5>{\rightarrow \langle X\ind{1}\ X\ind{2},\ X\ind{1}\ X\ind{2} \rangle} \\ - \alert<7>{X} & \alert<7>{\rightarrow \langle X\ind{1}\ X\ind{2},\ X\ind{2}\ X\ind{1} \rangle} & &\\ - \alert<4>{X} & \alert<4>{\rightarrow \langle Sie,\ She \rangle} - &\quad \alert<6>{X} & \alert<6>{\rightarrow \langle will,\ wants\ to \rangle} \\ - \alert<8>{X} & \alert<8>{\rightarrow \langle eine\ Tasse\ Kaffee,\ a\ cup\ of\ coffee \rangle} - &\quad \alert<9>{X} & \alert<9>{\rightarrow \langle trinken,\ drink\rangle} \\ - \end{align*} - \end{figure} - \end{block} - \begin{exampleblock}{Example Derivation} - %\begin{figure} - %\begin{align*} - \center - \vspace{0.2cm} - \onslide<2->{\alert<2>{$S \Rightarrow \langle X\ind{1},\ X\ind{1}\ \rangle$}} \quad \onslide<3->{\alert<3>{$\Rightarrow \langle X\ind{2}\ X\ind{3},\ X\ind{2}\ X\ind{3} \rangle$ \\}} - \vspace{0.2cm} - \onslide<4->{\alert<4>{$\Rightarrow \langle Sie\ X\ind{3},\ She\ X\ind{3} \rangle$}} \quad \onslide<5->{\alert<5>{$\Rightarrow \langle Sie\ X\ind{4}\ X\ind{5},\ She\ X\ind{4}\ X\ind{5} \rangle$ \\}} - \vspace{0.2cm} - \onslide<6->{\alert<6>{$\Rightarrow \langle Sie\ will\ X\ind{5},\ She\ wants\ to\ X\ind{5} \rangle$ }} \quad \onslide<7->{\alert<7>{$\Rightarrow \langle Sie\ will\ X\ind{6} X\ind{7},\ She\ wants\ to\ X\ind{7} X\ind{6} \rangle$ \\}} - \vspace{0.2cm} - \onslide<8->{\alert<8>{$\Rightarrow \langle Sie\ will\ eine\ Tasse\ Kaffee\ X\ind{7},\ She\ wants\ to\ X\ind{7}\ a\ cup\ of\ coffee\rangle$} \\} - \vspace{0.2cm} - \onslide<9->{\alert<9>{$\Rightarrow \langle Sie\ will\ eine\ Tasse\ Kaffee\ trinken,\ She\ wants\ to\ drink\ a\ cup\ of\ coffee\rangle$}} - \vspace{0.2cm} - %\end{align*} - %\end{figure} - \end{exampleblock} -\end{frame} - - -\begin{frame}[t]{Models of translation} -\begin{block}{Unlabelled SCFG: Hiero} - \begin{center} - \includegraphics[scale=0.55]{JeNeVeuxPasTravailler-Hiero.pdf} - \hspace{0.3in} - \includegraphics[scale=0.55]{JeVeuxTravailler-Hiero.pdf} - \end{center} -\end{block} -\begin{unpacked_itemize} -\only<1>{\item S -> $\langle$ X\ind{1}, X\ind{1} $\rangle$, \\ S -> $\langle$ S\ind{1} X\ind{2}, S\ind{1} X\ind{2} $\rangle$} -\only<1>{\item X -> $\langle$ Je, I $\rangle$, \hspace{0.5in} X -> $\langle$ ne X\ind{1} pas, do not X\ind{1} $\rangle$, \\ X -> $\langle$ veux, want to$\rangle$, X -> $\langle$ travailler, work $\rangle$} -\only<2->{ -\item Only requires the parallel corpus. -\item But weak model of sentence structure. -} -\end{unpacked_itemize} -\end{frame} - -\begin{frame}[t]{Models of translation} -\begin{exampleblock}{Supervised SCFG: Syntactic Tree-to-String} -\begin{center} - \includegraphics[scale=0.55]{JeNeVeuxPasTravailler-tsg.pdf} - \hspace{0.3in} - \includegraphics[scale=0.55]{JeVeuxTravailler-tsg.pdf} -\end{center} -\end{exampleblock} -\begin{itemize} -\only<1>{\item S -> $\langle$ NP\ind{1} VP\ind{2}, NP\ind{1} VP\ind{2} $\rangle$, \\ NP -> $\langle$ PRP\ind{1}, PRP\ind{1} $\rangle$} -\only<1>{\item PRP -> $\langle$ Je, I $\rangle$, VB -> $\langle$ travailler, work $\rangle$ \\ VP -> $\langle$ ne veux pas VB\ind{1}, do not want to VB\ind{1} $\rangle$} -\only<2->{ - \item Strong model of sentence structure. - \item Reliant on a treebank to train the parser. -} -\end{itemize} -\end{frame} - - -\begin{frame}[t]{Impact} -\vspace{0.5in} -\begin{table} - \begin{tabular}{l|rr} - \hline - Language & Words & Domain \\ \hline - English & 4.5M& Financial news \\ - Chinese & 0.5M & Broadcasting news \\ - Arabic & 300K (1M planned) & News \\ - Korean & 54K & Military \\ \hline - \end{tabular} -\caption{Major treebanks: data size and domain \label{table_treebanks_size}} -\end{table} -\end{frame} - - -\begin{frame}[t]{Impact} -Parallel corpora far exceed treebanks (millions of words): - \begin{figure} - {\centering \includegraphics[scale=0.7]{resource_matrix.pdf}} - \end{figure} -\end{frame} - - -\begin{frame}[t]{Models of translation} -\begin{exampleblock}{Phrase extraction:} -\begin{center} -\only<1>{\includegraphics[scale=0.8]{PhraseExtraction6.pdf}\\[1cm]} -\only<2>{\includegraphics[scale=0.8]{PhraseExtraction5.pdf}\\[1cm]} -\only<3>{\includegraphics[scale=0.8]{PhraseExtraction4.pdf}\\[1cm]} -\only<4>{\includegraphics[scale=0.8]{PhraseExtraction3.pdf}\\[1cm]} -\only<5>{\includegraphics[scale=0.8]{PhraseExtraction2.pdf}\\[1cm]} -\only<6>{\includegraphics[scale=0.8]{PhraseExtraction1.pdf}\\[1cm]} -\only<7>{\includegraphics[scale=0.8]{PhraseExtraction.pdf}\\[1cm]} -\end{center} -\end{exampleblock} -\only<2->{ -\begin{unpacked_itemize} -\only<2>{\item Use a word-based translation model to annotate the parallel corpus with word-alignments} -\only<3->{\item $\langle$ Je, I $\rangle$, $\langle$ veux, want to $\rangle$, $\langle$ travailler, work $\rangle$}\only<4->{, $\langle$ ne veux pas, do not want to $\rangle$}\only<5->{, $\langle$ ne veux pas travailler, do not want to work $\rangle$}\only<6->{, $\langle$ Je ne veux pas, I do not want to $\rangle$}\only<7->{, $\langle$ Je ne veux pas travailler, I do not want to work $\rangle$} -\end{unpacked_itemize} -} -\end{frame} - - -\begin{frame}[t]{Models of translation} -\begin{exampleblock}{SCFG Rule extraction:} -\begin{center} -\only<1>{\includegraphics[scale=0.8]{HieroExtraction1.pdf}\\[1cm]} -\only<2>{\includegraphics[scale=0.8]{HieroExtraction2.pdf}\\[1cm]} -\only<3>{\includegraphics[scale=0.8]{HieroExtraction3.pdf}\\[1cm]} -\only<4>{\includegraphics[scale=0.8]{HieroExtraction4.pdf}\\[1cm]} -\end{center} -\end{exampleblock} -\begin{unpacked_itemize} -\only<1>{ \item X -> $\langle$ ne veux pas, do not want to $\rangle$ } -\only<2>{ \item X -> $\langle$ ne veux pas, do not want to $\rangle$, \item X -> $\langle$ ne X\ind{1} pas, do not X\ind{1} $\rangle$ } -\only<3>{ \item VP$/$NN -> $\langle$ ne veux pas, do not want to $\rangle$, \item VP$/$NN -> $\langle$ ne V\ind{1} pas, do not V\ind{1} $\rangle$ } -\only<4>{ \item X10 -> $\langle$ ne veux pas, do not want to $\rangle$, \item X10 -> $\langle$ ne X14\ind{1} pas, do not X14\ind{1} $\rangle$ } -\end{unpacked_itemize} -\end{frame} - -\begin{frame}[t]{Models of translation} -\vspace{0.25in} -\begin{block}{This workshop} - \begin{center} - \includegraphics[scale=0.55]{JeNeVeuxPasTravailler-Hiero-labelled.pdf} - \hspace{0.3in} - \includegraphics[scale=0.55]{JeVeuxTravailler-Hiero-labelled.pdf} - \end{center} -\end{block} -\begin{unpacked_itemize} -\only<1>{\item S -> $\langle$ X4\ind{1} X2\ind{2}, X4\ind{1} X2\ind{2} $\rangle$, X4 -> $\langle$ X1\ind{1} X10\ind{2}, X1\ind{1} X10\ind{2} $\rangle$} -\only<1>{\item X1 -> $\langle$ Je, I $\rangle$, X10 -> $\langle$ ne X14\ind{1} pas, do not X14\ind{1} $\rangle$, \\ X14 -> $\langle$ veux, want to$\rangle$, X10 -> $\langle$ travailler, work $\rangle$} -\only<2->{ - \item Only requires the parallel corpus. - \item But also gives a strong model of sentence structure. -} -\end{unpacked_itemize} -\end{frame} - - -\begin{frame}[t]{Workshop overview} -Input: - \begin{itemize} -% \item Joshua decoder - \item Existing procedures for unlabelled synchronous grammar extraction - \end{itemize} -\vspace{0.3in} -Output: - \begin{itemize} - \item New unsupervised models for large scale synchronous grammar extraction, -% \item An implementation of this model, - \item A comparison and analysis of the existing and proposed models, - \item Extended decoders (cdec/Joshua) capable of working efficiently with these models. - \end{itemize} -\end{frame} - - -%\begin{frame}[t]{Models of translation} -%\begin{block}{Hierarchical} -% \begin{center} -% \includegraphics[scale=0.55]{JeNeVeuxPasTravailler-Hiero.pdf} -% \hspace{0.3in} -% \includegraphics[scale=0.55]{JeVeuxTravailler-Hiero.pdf} -% \end{center} -%\end{block} -%\end{frame} - - -%\begin{frame}[t]{Impact} -% \begin{center} -% \includegraphics[scale=0.3]{ccb_tree.pdf} -% \end{center} -%\end{frame} - - - -%\begin{frame}[t]{Models of translation} -%\vspace{0.25in} -%\begin{block}{Hierarchical} -% \begin{center} -% \includegraphics[scale=0.55]{JeNeVeuxPasTravailler-Hiero-labelled.pdf} -% \hspace{0.3in} -% \includegraphics[scale=0.55]{JeVeuxTravailler-Hiero-labelled.pdf} -% \end{center} -%\end{block} -%%\begin{itemize} -%%\item \alert{AIM: Implement a large scale open-source synchronous constituent learning system.} -%%\item \alert{AIM: Investigate and understand the relationship between the choice of synchronous grammar and SMT performance,} -%%\item \alert{AIM: and fix our decoders accordingly.} -%%\end{itemize} -%\end{frame} -% -%\begin{frame}[t]{Evaluation goals} -%We will predominately evaluate using BLEU, but also use automatic structured metrics and perform small scale human evaluation: -%\vspace{0.25in} -%\begin{unpacked_itemize} -%\item Evaluate phrasal, syntactic, unsupervised syntactic, -%\item Aim 1: Do no harm (not true of existing syntactic approach) -%\item Aim 2: Exceed the performance of current non-syntactic systems. -%\item Aim 3: Meet or exceed performance of existing syntactic systems. -%\end{unpacked_itemize} -%\end{frame} - -%\begin{frame}[t]{Impact} -%Success will have a significant impact on two areas of CL: -%\vspace{0.25in} -%\begin{unpacked_itemize} -%\item Machine translation -%\begin{unpacked_itemize} -% \item Make the benefits of richly structured translation models available to a much wider range of researchers and for a wider range of languages. -%% \item Change the research outlook of the field. -%\end{unpacked_itemize} -%\item Grammar induction: -%\begin{unpacked_itemize} -% \item Provide an empirical validation of state-of-the-art grammar induction techniques. -%\end{unpacked_itemize} -%\end{unpacked_itemize} -%\end{frame} - - -\begin{frame}[t]{Workshop Streams} -\begin{enumerate} -\item Implement scalable labelled SCFG grammar induction algorithms: -\begin{itemize} -\item by clustering translation phrases which occur in the same context we can learn which phrases are substituteable, -\item we have implemented both parametric and non-parametric Bayesian clustering algorithms. -\end{itemize} -\item Improve SCFG decoders to efficiently handle the grammars produced: -\begin{itemize} -\item translation complexity scales quadratically as we add more categories, -\item in order to decode efficiently with the grammars we've induced we have created faster search algorithms tuned for syntactic grammars. -\end{itemize} -\item Investigate discriminative training regimes to leverage features extracted from these grammars: -\begin{itemize} -\item to make the most of our induced grammars we need discriminative training algorithms that learn from more than a handful of features, -\item we've implemented two large scale discriminative algorithms for training our models. -\end{itemize} -\end{enumerate} -\end{frame} - -\begin{frame}[t]{Extrinsic evaluation: Bleu} -\begin{exampleblock}{ - \only<1>{Ngram overlap metrics:} - \only<2>{Ngram overlap metrics: 1-gram precision $p_1 = \frac{11}{14}$} - \only<3>{Ngram overlap metrics: 2-gram precision $p_2 = \frac{5}{13}$} - \only<4>{Ngram overlap metrics: 3-gram precision $p_3 = \frac{2}{12}$} - \only<5>{Ngram overlap metrics: 4-gram precision $p_4 = \frac{1}{11}$} -} -\vspace{0.2cm} -{\em Source}: \begin{CJK}欧盟 办事处 与 澳洲 大使馆 在 åŒ ä¸€ 建筑 内 \end{CJK} \\ -\vspace{0.3cm} -\only<1>{{\em Candidate}: the chinese embassy in australia and the eu representative office in the same building} -\only<2>{{\em Candidate}: \alert{the} chinese \alert{embassy} \alert{in} australia \alert{and} \alert{the} \alert{eu} representative \alert{office} \alert{in} \alert{the} \alert{same} \alert{building}} -\only<3>{{\em Candidate}: the chinese embassy in australia \alert{and} \alert{the} \alert{eu} representative office \alert{in} \alert{the} \alert{same} \alert{building}} -\only<4>{{\em Candidate}: the chinese embassy in australia and the eu representative office \alert{in} \alert{the} \alert{same} \alert{building}} -\only<5>{{\em Candidate}: the chinese embassy in australia and the eu representative office \alert{in} \alert{the} \alert{same} \alert{building}} -\vspace{0.2cm} -\end{exampleblock} - -\begin{block}{Reference Translations:} - \begin{enumerate} - \only<1>{\item the eu office and the australian embassy are housed in the same building} - \only<2>{\item \alert{the} \alert{eu} \alert{office} \alert{and} \alert{the} australian \alert{embassy} are housed \alert{in} \alert{the} \alert{same} \alert{building}} - \only<3>{\item \alert{the} \alert{eu} office \alert{and} \alert{the} australian embassy are housed \alert{in} \alert{the} \alert{same} \alert{building}} - \only<4>{\item the eu office and the australian embassy are housed \alert{in} \alert{the} \alert{same} \alert{building}} - \only<5>{\item the eu office and the australian embassy are housed \alert{in} \alert{the} \alert{same} \alert{building}} - - \only<1>{\item the european union office is in the same building as the australian embassy} - \only<2>{\item \alert{the} european union \alert{office} is \alert{in} \alert{the} \alert{same} \alert{building} as \alert{the} australian \alert{embassy}} - \only<3>{\item the european union office is \alert{in} \alert{the} \alert{same} \alert{building} as the australian embassy} - \only<4>{\item the european union office is \alert{in} \alert{the} \alert{same} \alert{building} as the australian embassy} - \only<5>{\item the european union office is \alert{in} \alert{the} \alert{same} \alert{building} as the australian embassy} - - \only<1>{\item the european union 's office and the australian embassy are both located in the same building} - \only<2>{\item \alert{the} european union 's \alert{office} \alert{and} \alert{the} australian \alert{embassy} are both located \alert{in} \alert{the} \alert{same} \alert{building}} - \only<3>{\item the european union 's office \alert{and} \alert{the} australian embassy are both located \alert{in} \alert{the} \alert{same} \alert{building}} - \only<4>{\item the european union 's office and the australian embassy are both located \alert{in} \alert{the} \alert{same} \alert{building}} - \only<5>{\item the european union 's office and the australian embassy are both located \alert{in} \alert{the} \alert{same} \alert{building}} - - \only<1>{\item the eu 's mission is in the same building with the australian embassy} - \only<2>{\item \alert{the} \alert{eu} 's mission is \alert{in} \alert{the} \alert{same} \alert{building} with \alert{the} australian \alert{embassy}} - \only<3>{\item \alert{the} \alert{eu} 's mission is \alert{in} \alert{the} \alert{same} \alert{building} with the australian embassy} - \only<4>{\item the eu 's mission is \alert{in} \alert{the} \alert{same} \alert{building} with the australian embassy} - \only<5>{\item the eu 's mission is \alert{in} \alert{the} \alert{same} \alert{building} with the australian embassy} - \end{enumerate} -\end{block} -\end{frame} - -\begin{frame}[t]{Extrinsic evaluation: Bleu} -\begin{exampleblock}{BLEU} -\Large -\begin{align} -\nonumber BLEU_n = BP \times \exp{\left( \sum_{n=1}^{N} w_n \log{p_n} \right) }\\ -\nonumber BP = \left\{ - \begin{array}{ll} - 1 & \mbox{if $c > r$} \\ - \exp{(1-\frac{R'}{C'})} & \mbox{if $c <= r$} - \end{array} \right. -\end{align} -\end{exampleblock} -\begin{itemize} -\item {\em BP} is the {\em Brevity Penalty}, $w_n$ is the ngram length weights (usually $\frac{1}{n}$), $p_n$ is precision of ngram predictions, $R'$ is the total length of all references and $C'$ is the sum of the best matching candidates. -\item statistics are calculate over the whole {\em document}, i.e. all the sentences. -\end{itemize} -\end{frame} - - - -\begin{frame}[t]{Language pairs} -\begin{unpacked_itemize} -\item BTEC Chinese-English: - \begin{itemize} - \item 44k sentence pairs, short sentences - \item Widely reported `prototyping' corpus - \item Hiero baseline score: 57.0 (16 references) - \end{itemize} -\item NIST Urdu-English: - \begin{itemize} - \item 50k sentence pairs - \item Hiero baseline score: 21.1 (4 references) - \item Major challenges: major long-range reordering, SOV word order - \end{itemize} -\item Europarl Dutch-French: - \begin{itemize} - \item 100k sentence pairs, standard Europarl test sets - \item Hiero baseline score: Europarl 2008 - 15.75 (1 reference) - \item Major challenges: V2 / V-final word order, morphology - \end{itemize} -\end{unpacked_itemize} -\end{frame} - - -\begin{frame}[t]{Outline} -\begin{columns} - \begin{column}{0.2\textwidth} - \begin{exampleblock}{} - \begin{figure} - \tiny - {\centering \includegraphics[scale=0.07]{trevor.jpg}} \\ - Trevor Cohn \\ - - {\centering \includegraphics[scale=0.06]{dyer.jpg}} \\ - Chris Dyer\\ - - {\centering \includegraphics[scale=0.11]{jan.jpg}} \\ - Jan Botha \\ - - {\centering \includegraphics[scale=0.06]{olivia.jpg}} \\ - Olivia Buzek\\ - - {\centering \includegraphics[scale=0.10]{desai.jpg}}\\ - Desai Chen\\ - - \end{figure} - \end{exampleblock} - %\vspace{0.25in} - \end{column} - \begin{column}{0.7\textwidth} - \begin{unpacked_itemize} - \item 1:55pm Grammar induction and evaluation. Trevor - \item 2:10pm Non-parametric models of category induction. Chris - \item 2:25pm Inducing categories for morphology. Jan - \item 2:35pm Smoothing, backoff and hierarchical grammars. Olivia - \item 2:45pm Parametric models: posterior regularisation. Desai - \item 3:00pm Break. - \end{unpacked_itemize} - \end{column} -\end{columns} -\end{frame} - - - -\begin{frame}[t]{Outline} -\begin{columns} - \begin{column}{0.2\textwidth} - \begin{exampleblock}{} - \begin{figure} - \tiny - {\centering \includegraphics[scale=0.05]{vlad.jpg}} \\ - Vlad Eidelman\\ - - {\centering \includegraphics[scale=0.15]{ziyuan.pdf}} \\ - Ziyuan Wang\\ - - {\centering \includegraphics[scale=0.06]{adam.jpg}} \\ - Adam Lopez\\ - - {\centering \includegraphics[scale=0.10]{jon.pdf}} \\ - Jon Graehl\\ - - {\centering \includegraphics[scale=0.15]{linh.pdf}} \\ - ThuyLinh Nguyen\\ - - \end{figure} - \end{exampleblock} - \end{column} - \begin{column}{0.7\textwidth} - \begin{itemize} - \setlength{\itemsep}{25pt} - \setlength{\parskip}{0pt} - \setlength{\parsep}{0pt} - \item 3:15pm Training models with rich features spaces. Vlad - \item 3:30pm Decoding with complex grammars. Adam - \item 4:00pm Closing remarks. Phil - \item 4:05pm Finish. - \end{itemize} - \end{column} -\end{columns} -\end{frame} - - - -\begin{frame}[t]{Remember:} - \vspace{0.5in} - \begin{unpacked_itemize} - \item Idea: Learn synchronous grammar labels which encode substituteability; phrases which occur in the same context should receive the same label. - \item Result: Better models of translation structure, morphology and improved decoding algorithms. - \end{unpacked_itemize} -\end{frame} - - -\begin{frame}[t]{Outline} -\begin{columns} - \begin{column}{0.2\textwidth} - \begin{exampleblock}{} - \begin{figure} - \tiny - {\centering \includegraphics[scale=0.07]{trevor.jpg}} \\ - Trevor Cohn \\ - - {\centering \includegraphics[scale=0.06]{dyer.jpg}} \\ - Chris Dyer\\ - - {\centering \includegraphics[scale=0.11]{jan.jpg}} \\ - Jan Botha \\ - - {\centering \includegraphics[scale=0.06]{olivia.jpg}} \\ - Olivia Buzek\\ - - {\centering \includegraphics[scale=0.10]{desai.jpg}}\\ - Desai Chen\\ - - \end{figure} - \end{exampleblock} - %\vspace{0.25in} - \end{column} - \begin{column}{0.7\textwidth} - \begin{unpacked_itemize} - \only<1>{\item \alert{1:55pm Grammar induction and evaluation. Trevor}} - \only<2->{\item 1:55pm Grammar induction and evaluation. Trevor} - \only<2>{\item \alert{2:10pm Non-parametric models of category induction. Chris}} - \only<1,3->{\item 2:10pm Non-parametric models of category induction. Chris} - \only<3>{\item \alert{2:25pm Inducing categories for morphology. Jan}} - \only<1,2,4->{\item 2:25pm Inducing categories for morphology. Jan} - \only<4>{\item \alert{2:35pm Smoothing, backoff and hierarchical grammars. Olivia}} - \only<1-3,5->{\item 2:35pm Smoothing, backoff and hierarchical grammars. Olivia} - \only<5>{\item \alert{2:45pm Parametric models: posterior regularisation. Desai}} - \only<1-4,6->{\item 2:45pm Parametric models: posterior regularisation. Desai} - \only<6>{\item \alert{3:00pm Break.}} - \only<1-5>{\item 3:00pm Break.} - \end{unpacked_itemize} - \end{column} -\end{columns} -\end{frame} - - - -\begin{frame}[t]{Outline} -\begin{columns} - \begin{column}{0.2\textwidth} - \begin{exampleblock}{} - \begin{figure} - \tiny - {\centering \includegraphics[scale=0.05]{vlad.jpg}} \\ - Vlad Eidelman\\ - - {\centering \includegraphics[scale=0.15]{ziyuan.pdf}} \\ - Ziyuan Wang\\ - - {\centering \includegraphics[scale=0.06]{adam.jpg}} \\ - Adam Lopez\\ - - {\centering \includegraphics[scale=0.10]{jon.pdf}} \\ - Jon Graehl\\ - - {\centering \includegraphics[scale=0.15]{linh.pdf}} \\ - ThuyLinh Nguyen\\ - - \end{figure} - \end{exampleblock} - \end{column} - \begin{column}{0.7\textwidth} - \begin{itemize} - \setlength{\itemsep}{25pt} - \setlength{\parskip}{0pt} - \setlength{\parsep}{0pt} - \only<1>{\item \alert{3:20pm Parametric models: posterior regularisation. Desai}} - \only<2->{\item 3:20pm Parametric models: posterior regularisation. Desai} - \only<2>{\item \alert{3:35pm Training models with rich features spaces. Vlad}} - \only<1,3->{\item 3:35pm Training models with rich features spaces. Vlad} - \only<3>{\item \alert{3:50pm Decoding with complex grammars. Adam}} - \only<1,2,4->{\item 3:50pm Decoding with complex grammars. Adam} - \only<4>{\item \alert{4:20pm Closing remarks. Phil}} - \only<1-3,5->{\item 4:20pm Closing remarks. Phil} - \only<5>{\item \alert{4:25pm Finish.}} - \only<1-4>{\item 4:25pm Finish.} - \end{itemize} - \end{column} -\end{columns} -\end{frame} - - -\end{document} diff --git a/report/intro_slides/full_of_fun_hiero.graffle b/report/intro_slides/full_of_fun_hiero.graffle deleted file mode 100644 index 4dde7f4e..00000000 --- a/report/intro_slides/full_of_fun_hiero.graffle +++ /dev/null @@ -1,2788 +0,0 @@ - - - - - ActiveLayerIndex - 0 - AutoAdjust - - CanvasColor - - w - 1 - - CanvasOrigin - {0, 0} - CanvasScale - 1 - ColumnAlign - 1 - ColumnSpacing - 36 - CreationDate - 2009-04-22 17:41:04 +0100 - Creator - Trevor Cohn - DisplayScale - 1 cm = 1 cm - GraphDocumentVersion - 5 - GraphicsList - - - Class - LineGraphic - Head - - ID - 467 - - ID - 477 - Points - - {454.08, 412.606} - {426.153, 313.083} - - Style - - stroke - - HeadArrow - 0 - TailArrow - 0 - - - Tail - - ID - 242 - - - - Class - LineGraphic - Head - - ID - 205 - - ID - 473 - Points - - {431.29, 313.083} - {519.469, 412.727} - - Style - 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-\f0\fs12 \cf0 All Gaul is divided into three parts, one of which the Belgae inhabit, the Aquitani another, those who in their own language are called Celts, in our Gauls, the third. 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-\mode -{ - \usetheme{Boadilla} - \setbeamercovered{transparent}} - -\usepackage[english]{babel} -\usepackage{times} - -\usepackage{xcolor} -\usepackage{colortbl} -%\usepackage{subfigure} - -\usepackage{fontspec} -\usepackage{xunicode} -\usepackage{xltxtra} -\usepackage{booktabs} -\newenvironment{CJK}{\fontspec[Scale=0.9]{PMingLiU}}{} -\newenvironment{Geeza}{\fontspec[Scale=0.9]{Geeza Pro}}{} - -%% for tables -\newcommand{\mc}{\multicolumn} -\newcommand{\lab}[1]{\multicolumn{1}{c}{#1}} -\newcommand{\ind}[1]{{\fboxsep1pt\raisebox{-.5ex}{\fbox{{\tiny #1}}}}} -\newcommand{\IND}[1]{{\fboxsep1pt\raisebox{0ex}{\fbox{{\small #1}}}}} -\newcommand\production[2]{\ensuremath{\langle\mbox{#1}, \mbox{#2}\rangle}} - -%% markup -\newcommand{\buffer}[1]{{\color{blue}\textbf{#1}}} -\newcommand{\pred}[1]{\code{#1}} - -%% colors -\newcommand{\textred}[1]{\alert{#1}} -\newcommand{\textblue}[1]{\buffer{#1}} -\definecolor{tablecolor}{cmyk}{0,0.3,0.3,0} -\newcommand{\keytab}[1]{\mc{1}{>{\columncolor{tablecolor}}d}{#1}} - -% rules -\newcommand{\psr}[2]{#1 $\rightarrow \langle $ #2 $\rangle$} - -\newenvironment{unpacked_itemize}{ -\begin{itemize} - \setlength{\itemsep}{10pt} - \setlength{\parskip}{0pt} - \setlength{\parsep}{0pt} -}{\end{itemize}} - -\newcommand{\condon}{\hspace{0pt} | \hspace{1pt}} -\definecolor{darkblue}{rgb}{0,0,0.6} -\newcommand{\blueexample}[1]{\textcolor{darkblue}{\rm #1}} - -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -\newcommand{\ws}{\ensuremath{\vec{w}}} -\newcommand{\pu}{\ensuremath{P_0}} -\newcommand{\bx}{\mathbf{x}} -\newcommand{\bz}{\mathbf{z}} -\newcommand{\bd}{\mathbf{d}} -\newcommand{\by}{\mathbf{y}} -\newcommand\bleu{${B{\scriptstyle LEU}}$} - - -\title[Models of SCFG Induction]{Models of Synchronous Grammar Induction for SMT} - -\author[CLSP Workshop 2010]{ - Workshop 2010 - %Phil Blunsom$^1$ \and Trevor Cohn$^2$ \and Chris Dyer$^3$ \and Adam Lopez$^4$ -} - -\institute[Baltimore]{ - The Center for Speech and Language Processing \\ Johns Hopkins University -% $^1$University of Oxford\\ -% $^2$University of Sheffield\\ -% $^3$Carnegie Mellon University\\ -% $^4$University of Edinburgh -} -\date[June 21]{June 21, 2010} - -%\subject{Unsupervised models of Synchronous Grammar Induction for SMT} - -%\pgfdeclareimage[height=1.0cm]{university-logo}{logo} -%\logo{\pgfuseimage{university-logo}} - -%\AtBeginSection[] -%{ -% \begin{frame}{Outline} -% %\tableofcontents[currentsection,currentsubsection] -% \tableofcontents[currentsection] -% \end{frame} -%} - -%\beamerdefaultoverlayspecification{<+->} - -\begin{document} - -\begin{frame} - \titlepage -\end{frame} - -%\begin{frame}{Outline} -% \tableofcontents -% You might wish to add the option [pausesections] -%\end{frame} - -%\begin{frame}{Outline} -% \tableofcontents -% % You might wish to add the option [pausesections] -%\end{frame} - - -\begin{frame}[t]{Team members} -\begin{center} -{\bf Senior Members} \\ - Phil Blunsom (Oxford)\\ - Trevor Cohn (Sheffield)\\ - Adam Lopez (Edinburgh/COE)\\ - Chris Dyer (CMU)\\ - Jonathan Graehl (ISI)\\ -\vspace{0.2in} -{\bf Graduate Students} \\ - Jan Botha (Oxford) \\ - Vladimir Eidelman (Maryland) \\ - Ziyuan Wang (JHU) \\ - ThuyLinh Nguyen (CMU) \\ -\vspace{0.2in} -{\bf Undergraduate Students} \\ - Olivia Buzek (Maryland) \\ - Desai Chen (CMU) \\ -\end{center} -\end{frame} - - - -\begin{frame}[t]{Statistical machine translation} -%\vspace{1.0cm} -\begin{exampleblock}{Arabic $\rightarrow$ English} - \begin{figure} - {\centering \includegraphics[scale=0.55]{arabic.pdf}} - \end{figure} -\vspace{0.10cm} -\end{exampleblock} -\begin{itemize} - \item Statistical machine translation: Learn how to translate from parallel corpora. -\end{itemize} -\end{frame} - - -\begin{frame}[t]{Statistical machine translation: successes} -%\vspace{1.0cm} -\begin{exampleblock}{Arabic $\rightarrow$ English} - \begin{figure} - {\centering \includegraphics[scale=0.55]{arabic-good.pdf}} - \end{figure} -\end{exampleblock} -\begin{itemize} - \item Statistical machine translation: Learn how to translate from parallel corpora -\end{itemize} -\end{frame} - -\begin{frame}[t]{Statistical machine translation: limitations} -%\vspace{1.0cm} -\begin{alertblock}{Chinese $\rightarrow$ English} - \begin{figure} - {\centering \includegraphics[scale=0.7]{chinese-bad.pdf}} - \end{figure} -\end{alertblock} -\begin{itemize} - \item This workshop: Learn to do it better. -\end{itemize} -\end{frame} - - -\begin{frame}[t]{Statistical machine translation: limitations} -\vspace{1.0cm} -\begin{exampleblock}{Structural divergence between languages:} - %\vspace{0.3cm} - \begin{table} - \centering - \only<1>{ - \begin{tabular}{|l|l|} - \hline -% {\bf English} & {\bf The plane is faster than the train.}\\ -% \hline -% Arabic & \begin{Geeza}الطائرة أسرع من القطار\end{Geeza} \\ -% & (the-plane) (faster) (than) (the train) \\ -% \hline -% Chinese & \begin{CJK}飞机 比 ç«è½¦ å¿«\end{CJK} \\ -% & (plane) (compared-to) (train) (fast) \\ -% \hline -% \hline - {\bf English} & {\bf Who wrote this letter?} \\ - \hline - Arabic & \begin{Geeza}من الذي كتب هذه الرسالة؟\end{Geeza} \\ - & \textcolor{gray}{(function-word)} (who) (wrote) (this) (the-letter) \\ - \hline - Chinese & \begin{CJK}è¿™å° ä¿¡ 是 è° å†™ çš„ ？\end{CJK} \\ - & (this) (letter) (be) (who) (write) (come-from) \textcolor{gray}{(function-word)} \\ - \hline - \end{tabular} - } - \only<2>{ - \begin{tabular}{|l|l|} - \hline - {\bf English} & {\bf \textcolor{blue}{Who} \textcolor{green}{wrote} \textcolor{red}{this} \textcolor{orange}{letter?}} \\ - \hline - Arabic & \begin{Geeza}من الذي كتب هذه الرسالة؟\end{Geeza} \\ - & \textcolor{gray}{(function-word)} \textcolor{blue}{(who)} \textcolor{green}{(wrote)} \textcolor{red}{(this)} \textcolor{orange}{(the-letter)} \\ - \hline - Chinese & \begin{CJK}è¿™å° ä¿¡ 是 è° å†™ çš„ ？\end{CJK} \\ - & (this) (letter) (be) (who) (write) (come-from) \textcolor{gray}{(function-word)} \\ - \hline - \end{tabular} - } - \only<3->{ - \begin{tabular}{|l|l|} - \hline - {\bf English} & {\bf \textcolor{blue}{Who wrote} \textcolor{red}{this letter}?} \\ - \hline - Arabic & \begin{Geeza}من الذي كتب هذه الرسالة؟\end{Geeza} \\ - & \textcolor{gray}{(function-word)} (who) (wrote) (this) (the-letter) \\ - \hline - Chinese & \begin{CJK}\textcolor{red}{è¿™å° ä¿¡} \textcolor{blue}{是 è° å†™} çš„ ？\end{CJK} \\ - & \textcolor{red}{(this) (letter)} \textcolor{blue}{(be) (who) (write) (come-from)} \textcolor{gray}{(function-word)} \\ - \hline - \end{tabular} - } - \end{table} -\end{exampleblock} -\only<4>{ - \begin{itemize} - \item Phrasal translation equivalences \textcolor{green}{(existing models)} - \item {\bf Constituent reordering \textcolor{blue}{(this workshop!)}} - \item Morphology \textcolor{red}{(Next year?)} - \end{itemize} -} -\end{frame} - -\begin{frame}[t]{Statistical machine translation: successes} -\begin{center} - \includegraphics[scale=0.35]{GoogleTranslateLanguages.pdf} -\end{center} -\end{frame} - -\begin{frame}[t]{Workshop overview} -Input: - \begin{itemize} -% \item Joshua decoder - \item Existing procedures for synchronous grammar extraction - \end{itemize} -\vspace{0.3in} -Output: - \begin{itemize} - \item New unsupervised models for large scale synchronous grammar extraction, -% \item An implementation of this model, - \item A systematic comparison and analysis of the existing and proposed models, - \item Extended decoders (cdec/Joshua) capable of working efficiently with these models. - \end{itemize} -\end{frame} - -\begin{frame}[t]{Models of translation} -\begin{exampleblock}{Supervised SCFG: Syntactic Tree-to-String} -\begin{center} - \includegraphics[scale=0.55]{JeNeVeuxPasTravailler-tsg.pdf} - \hspace{0.3in} - \includegraphics[scale=0.55]{JeVeuxTravailler-tsg.pdf} -\end{center} -\end{exampleblock} -\begin{itemize} -\item Strong model of sentence structure. -\item Reliant on a treebank to train the parser. -\end{itemize} -\end{frame} - -\begin{frame}[t]{Models of translation} -\begin{block}{Unlabelled SCFG: Hiero} - \begin{center} - \includegraphics[scale=0.55]{JeNeVeuxPasTravailler-Hiero.pdf} - \hspace{0.3in} - \includegraphics[scale=0.55]{JeVeuxTravailler-Hiero.pdf} - \end{center} -\end{block} -\begin{itemize} -\item Only requires the parallel corpus. -\item But weak model of sentence structure. -\end{itemize} -\end{frame} - -%\begin{frame}[t]{Models of translation} -%\begin{block}{Hierarchical} -% \begin{center} -% \includegraphics[scale=0.55]{JeNeVeuxPasTravailler-Hiero.pdf} -% \hspace{0.3in} -% \includegraphics[scale=0.55]{JeVeuxTravailler-Hiero.pdf} -% \end{center} -%\end{block} -%\end{frame} - - -%\begin{frame}[t]{Impact} -% \begin{center} -% \includegraphics[scale=0.3]{ccb_tree.pdf} -% \end{center} -%\end{frame} - - -\begin{frame}[t]{Impact} -Systems using syntax have outperformed those that didn't: - \begin{center} - \includegraphics[scale=1.0]{ccb_graph1.pdf} - \end{center} -\end{frame} - - -\begin{frame}[t]{Impact} -\vspace{0.5in} -\begin{table} - \begin{tabular}{l|rr} - \hline - Language & Words & Domain \\ \hline - English & 4.5M& Financial news \\ - Chinese & 0.5M & Broadcasting news \\ - Arabic & 300K (1M planned) & News \\ - Korean & 54K & Military \\ \hline - \end{tabular} -\caption{Major treebanks: data size and domain \label{table_treebanks_size}} -\end{table} -\end{frame} - - -\begin{frame}[t]{Impact} -Parallel corpora far exceed treebanks (millions of words): - \begin{figure} - {\centering \includegraphics[scale=0.7]{resource_matrix.pdf}} - \end{figure} -\end{frame} - - -\begin{frame}[t]{Models of translation} -\begin{block}{Hierarchical} - \begin{center} - \includegraphics[scale=0.55]{JeNeVeuxPasTravailler-Hiero-labelled.pdf} - \hspace{0.3in} - \includegraphics[scale=0.55]{JeVeuxTravailler-Hiero-labelled.pdf} - \end{center} -\end{block} -\begin{itemize} -\item \alert{AIM: Implement a large scale open-source synchronous constituent learning system.} -\item \alert{AIM: Investigate and understand the relationship between the choice of synchronous grammar and SMT performance,} -\item \alert{AIM: and fix our decoders accordingly.} -\end{itemize} -\end{frame} - - -\begin{frame}[t]{Impact} -Systems using syntax have outperformed those that didn't: - \begin{center} - \includegraphics[scale=1.0]{ccb_graph2.pdf} - \end{center} -\end{frame} - -\begin{frame}[t]{Evaluation goals} -We will predominately evaluate using BLEU, but also use automatic structured metrics and perform small scale human evaluation: -\vspace{0.25in} -\begin{unpacked_itemize} -\item Evaluate phrasal, syntactic, unsupervised syntactic, -\item Aim 1: Do no harm (not true of existing syntactic approach) -\item Aim 2: Exceed the performance of current non-syntactic systems. -\item Aim 3: Meet or exceed performance of existing syntactic systems. -\end{unpacked_itemize} -\end{frame} - -%\begin{frame}[t]{Impact} -%Success will have a significant impact on two areas of CL: -%\vspace{0.25in} -%\begin{unpacked_itemize} -%\item Machine translation -%\begin{unpacked_itemize} -% \item Make the benefits of richly structured translation models available to a much wider range of researchers and for a wider range of languages. -%% \item Change the research outlook of the field. -%\end{unpacked_itemize} -%\item Grammar induction: -%\begin{unpacked_itemize} -% \item Provide an empirical validation of state-of-the-art grammar induction techniques. -%\end{unpacked_itemize} -%\end{unpacked_itemize} -%\end{frame} - - -\begin{frame}[t]{Workshop Streams} -\vspace{0.25in} -\begin{unpacked_itemize} -\item Implement scalable SCFG grammar extraction algorithms. -\item Improve SCFG decoders to effieciently handle the grammars produce. -\item Investigate discriminative training regimes the leverage features extracted from these grammars. -\end{unpacked_itemize} -\end{frame} - - -%\begin{frame}[t] -%\frametitle{Inducing a STSG given an observed tree:} -%\only<1>{\frametitle{Inducing a STSG given an observed tree:}} -%\only<2->{\frametitle{Existing approach (Galley et al. 2004):}} -% -%\begin{center} -% \only<1>{\hspace{1mm}\includegraphics[scale=0.45]{full_of_fun_slides_start.pdf}} -% \only<2>{\includegraphics[scale=0.45]{full_of_fun_slides_waligned.pdf}} -% \only<3>{\vspace{-2mm}\includegraphics[scale=0.45]{full_of_fun_slides_waligned_overlay.pdf}} -%% \only<4>{\includegraphics[scale=0.4]{full_of_fun_slides_third.pdf}} -%% \only<5>{\includegraphics[scale=0.4]{full_of_fun_slides_forth.pdf}} -% -% \only<1>{Training instance} -% \only<2>{Step 1: word alignment} -% \only<3>{Step 2: rule extraction heuristic} -%% \only<4>{Step 2: the rules extracted} -%% \only<5>{Step 3: estimate a grammar} -%\end{center} -%\end{frame} - - -% Il ne veut pas travailler - - -%\begin{frame}[t]{Models of translation} -%\begin{block}{Hierarchical} -% \begin{center} -% \includegraphics[scale=0.55]{JeNeVeuxPasTravailler-Hiero-labelled.pdf} -% \hspace{0.3in} -% \includegraphics[scale=0.55]{JeVeuxTravailler-Hiero-labelled.pdf} -% \end{center} -%\end{block} -%\begin{itemize} -%\item \alert{AIM: Implement a large scale open-source synchronous constituent labelling system.} -%\item \alert{AIM: Investigate and understand the relationship between synchronous constituency and SMT performance.} -%\end{itemize} -%\end{frame} -% -%\begin{frame}[t]{Models of translation} -%\begin{block}{Hierarchical} -% \begin{center} -% \includegraphics[scale=0.5]{JeNeVeuxPasTravailler-Hiero-labelled.pdf} -% \includegraphics[scale=0.5]{IlNeVeutPasTravailler-Hiero-labelled.pdf} -% \end{center} -% \vspace{0.001in} -%\end{block} -%\begin{itemize} -%\item \alert{AIM: Implement a large scale open-source synchronous constituent labelling system.} -%\item \alert{AIM: Investigate and understand the relationship between synchronous constituency and SMT performance.} -%\end{itemize} -%\end{frame} - -\begin{frame}[t]{Unsupervised grammar induction} -There has been significant research into monolingual grammar induction: -\vspace{0.1in} -\alert{Constituent context is a prime indicator of constituency.} -\begin{unpacked_itemize} -\item Alexander Clark. Unsupervised induction of stochastic context-free grammars using distributional clustering, 2001 -\item Dan Klein and Chris Manning. A Generative Constituent-Context Model for Improved Grammar Induction, 2002 -\end{unpacked_itemize} -\vspace{0.1in} -\alert{We can formalise this notion in algebraic structures} -\begin{itemize} -\item Alexander Clark. A learnable representation for syntax using residuated lattices, 2009 -\end{itemize} -\vspace{0.1in} -Deep connections to unsupervised word sense disambiguation, thesaurus extraction etc. -\end{frame} - -%\begin{frame}[t]{Monolingual grammar induction} -%Induce bracketing phrase-structure grammars: -% \includegraphics[scale=1]{klein_ccm.pdf} -% -%\vspace{2ex} -%And dependency trees: \\ -% \includegraphics[scale=1]{klein_dependency.pdf} -% -%\vspace{2ex} -%Informed by constituent context: surrounding words are a good indicator of substitutability -%\end{frame} - - -\begin{frame}[t]{SCFG Grammar Induction} -%\vspace{1.0cm} -\begin{exampleblock}{Distributional Hypothesis} -\begin{quote} -\emph{Words that occur in the same contexts tend to have similar meanings} -\end{quote} -\hfill (Zellig Harris, 1954) -\end{exampleblock} - -\vspace{3ex} - -We will leverage this in a translation setting: -\begin{itemize} - \item Use the contexts to \alert{cluster} translation units into groups - \item Units in the same group expected to be semantically and syntactically similar - \item Then use these cluster labels to guide translation - \begin{itemize} - \item lexical selection: translating ambiguous source word/s - \item reordering: consistent syntactic patterns of reordering - \end{itemize} -\end{itemize} -\end{frame} - -\begin{frame}[t]{Monolingual Example} -Task: cluster words into their parts-of-speech. \\ - -\vspace{1ex} -Illustrate by starting with the word `deal' (noun or verb): - -\only<1>{\includegraphics[width=\columnwidth]{deal_first.pdf} \\ Step 1: Find contexts for `deal'} -\only<2->{\includegraphics[width=\columnwidth]{deal.pdf} \\ Step 2: Find other words which occur in these contexts} -%\only<3>{\includegraphics[width=\columnwidth]{deal_more.pdf} \\ \ldots continue to expand} - -\only<3>{ -\vspace{1ex} -Notice that the instances of deal can be split into two connected sub-graphs: -\begin{itemize} - \item noun: the left two contexts ``a \ldots with'' and ``a \ldots that'' - \item verb: the right two contexts ``to \ldots with'' and ``not \ldots with'' - \item neighbouring words of these contexts share the same PoS -\end{itemize} -} - -\end{frame} - -%\begin{frame}[t]{More Formally} -% -%Construct a bipartite graph -%\begin{itemize} -% \item Nodes on the top layer denote word types (bilingual phrase pairs) -% \item Nodes on the bottom layer denote context types (monlingual/bilingual words) -% \item Edges connect words and their contexts -%\end{itemize} -% -%\includegraphics[width=\columnwidth]{bipartite.pdf} -% -%\end{frame} - -\begin{frame}[t]{Clustering} - -Task is to cluster the graph into sub-graphs. Nodes in the sub-graphs should be -\begin{itemize} -\item strongly connected to one another -\item weakly connected to nodes outside the sub-graph -\item could formulate as either \emph{hard} or \emph{soft} clustering -\end{itemize} -Choose \alert{soft clustering} to allow for syntactic and semantic ambiguity - -\centering -\includegraphics[width=0.7\columnwidth]{bipartite_lda.pdf} - -\end{frame} - -\begin{frame}[t]{Constituency and context} -\vspace{0.25in} -\begin{center} -\only<1>{ - \includegraphics[scale=0.5]{WantTo_Veux_context.pdf} - \includegraphics[scale=0.5]{WantTo_Veux_context2.pdf} -} -\only<2>{ - \includegraphics[scale=0.5]{WantTo_Veux_context_split.pdf} - \includegraphics[scale=0.5]{WantTo_Veux_context2_split.pdf} -} -\only<3>{ - \includegraphics[scale=0.5]{WantTo_Veux_context_split_mono.pdf} - \includegraphics[scale=0.5]{WantTo_Veux_context2_split_mono.pdf} -} -\end{center} -\vspace{0.1in} -%\only<1>{ -% There has been significant research into monolingual grammar induction: -% \vspace{0.1in} -% \begin{unpacked_itemize} -% \item Alexander Clark. Unsupervised induction of stochastic context-free grammars using distributional clustering, 2001 -% \item Dan Klein and Chris Manning. A Generative Constituent-Context Model for Improved Grammar Induction, 2002 -% \end{unpacked_itemize} -% \alert{Constituent context is a prime indicator of constituency.} -%} -%\only<1>{ -\begin{unpacked_itemize} -\item Design and apply large scale scale clustering and topic modelling algorithms (LDA, HDPs, HPYPs etc), -\item identify sets of frequent contexts that distinguish synchronous constituent properties. -\item Motivated by successful models of monolingual grammar induction, -\item deep connections to unsupervised word sense disambiguation, thesaurus extraction etc. -\end{unpacked_itemize} -%} -\end{frame} - -\begin{frame}[t]{Latent Dirichlet Allocation (LDA)} - -LDA is a generative model which treats documents as bags of words -\begin{itemize} - \item each word is assign a \alert{topic} (cluster tag) - \item words are generated from a topic-specific multinomial - \item topics are \alert{tied} across a document using a Dirichlet prior - \item $\alpha < 1$ biases towards \alert{sparse} distributions, i.e., topic reuse - \item inferred $\theta_d$ describes a document and $\phi_t$ describes a topic -\end{itemize} - -\vspace{-3ex} -\includegraphics[scale=0.55]{lda.pdf} - -\end{frame} - -\begin{frame}[t]{LDA over Contexts} - -Generative story: -\begin{itemize} - \item for each word type $w$ - \item for each of the $L$ contexts - \item first we draw a topic $t$, then generate the context $\vec{c}$ given the topic - \item the Dirichlet prior ties the topics for each $w$ - \item we're primarily interested in the learnt $\theta$ values -\end{itemize} - -\includegraphics[scale=0.4]{context_lda.pdf} - -\end{frame} - -\begin{frame}[t]{Scalable grammar extraction with MapReduce} -\begin{itemize} -\item Divide and conquer approach to...counting -\begin{itemize} -\item map function $\mathcal{M}(x) \rightarrow \langle k_1, v_1 \rangle, \langle k_2, v_2 \rangle, \ldots$ -\item write a reduce function $\mathcal{R}(k_i : v_7, v_{13} , \ldots) \rightarrow \langle k_i, \overline{v} \rangle$ -\end{itemize} -\end{itemize} -\begin{center} - \includegraphics[scale=0.4]{mroutline.pdf} -\end{center} -\end{frame} -\begin{frame}[t]{Scalable grammar extraction with MapReduce : mapper} -\begin{center} - \includegraphics[scale=0.4]{mapper.pdf} -\end{center} -\end{frame} - -\begin{frame}[t]{Scalable grammar extraction with MapReduce : reducer} -\begin{center} - \includegraphics[scale=0.4]{reducer.pdf} -\end{center} -\end{frame} - -\begin{frame}[t]{Scalable grammar extraction with MapReduce : Hadoop} -\begin{center} - \includegraphics[scale=0.4]{hadoop-extract.pdf} -\end{center} -\end{frame} - -\begin{frame}[t]{Scalable grammar extraction with MapReduce : Hadoop} -\begin{center} - \includegraphics[scale=0.4]{hadoop-extract-arrows.pdf} -\end{center} -\end{frame} - - -%\begin{frame}[t]{Discriminative training} -%\begin{unpacked_itemize} -%\item MIRA -%\item Expected loss minimisation. -%\end{unpacked_itemize} -%\end{frame} - - -\begin{frame}[t]{Language pairs (small)} -\begin{itemize} -\item BTEC Chinese-English: - \begin{itemize} - \item 44k sentence pairs, short sentences - \item Widely reported `prototyping' corpus - \item Hiero baseline score: 52.4 (16 references) - \item Prospects: BTEC always gives you good results - \end{itemize} -\item NIST Urdu-English: - \begin{itemize} - \item 50k sentence pairs - \item Hiero baseline score: MT05 - 23.7 (4 references) - \item Major challenges: major long-range reordering, SOV word order - \item Prospects: small data, previous gains with supervised syntax - \end{itemize} -\end{itemize} -\end{frame} - -\begin{frame}[t]{Language pairs (large)} -\begin{itemize} -\item NIST Chinese-English: - \begin{itemize} - \item 1.7M sentence pairs, Standard NIST test sets - \item Hiero baseline score: MT05 - 33.9 (4 references) - \item Major challenges: large data, mid-range reordering, lexical ambiguity - \item Prospects: supervised syntax gains reported - \end{itemize} -\item NIST Arabic-English: - \begin{itemize} - \item 900k sentence pairs - \item Hiero baseline score: MT05 - 48.9 (4 references) - \item Major challenges: strong baseline, local reordering, VSO word order - \item Prospects: difficult - \end{itemize} -\item Europarl Dutch-French: - \begin{itemize} - \item 1.5M sentence pairs, standard Europarl test sets - \item Hiero baseline score: Europarl 2008 - 26.3 (1 reference) - \item Major challenges: V2 / V-final word order, many non-literal translations - \item Prospects: ??? - \end{itemize} -\end{itemize} -\end{frame} - -%\begin{frame}[t]{Draft Schedule} -%\begin{itemize} -%\item Pre-workshop: -% \begin{itemize} -% \item Collect existing open-source tools for synchronous grammar induction, -% \item Collect corpora across a range of translations conditions: small, large, low-density languages etc. -% \item Implement phrase and context extraction algorithms. -% \item Design the integration of various existing approaches into the decoders. -% \end{itemize} -%\item Week 1: -% \begin{itemize} -% \item Optimise and reconfigure decoders to handle labelled synchronous grammars, -% \item Perform a empirical study of synchronous constituency models. -% \end{itemize} -%\end{itemize} -%\end{frame} - -%\begin{frame}[t]{Draft Schedule} -%\begin{itemize} -%\item Week 2-3: -% \begin{itemize} -% \item Continue optimising decoder to handle labelled synchronous grammars, -% \item Implement unsupervised label induction algorithms, initially inducing a single label per-phrase. -% \item Extend to ''topic"-modelling style representation where a phrase may have multiple labellings. -% \item Perform experimental comparison of existing synchronous grammar translation models. -% \end{itemize} -%\item Week 3-6: -% \begin{itemize} -% \item Perform experimental comparison of unsupervised synchronous grammar translation models. -% \item Extend the evaluation to small/big data sets, hi-density vs. low-density language pairs. -% \item Create ``semi-supervised'' models combining knowledge from treebank parser into the unsupervised algorithms. -% \item Wrap-up and write final report. -% \end{itemize} -%\end{itemize} -%\end{frame} - - -\begin{frame}[t]{Pre-workshop experiments} -\vspace{0.25in} -We have implemented a baseline constituent modelling and distrbuted grammar extraction pipeline. Initial results on the small BTEC corpora: - -\vspace{0.25in} -\begin{exampleblock} -\footnotesize -\centering -\begin{tabular}{lcccccc} -\toprule -Categories & \small 1-gram & \small 2-grams & \small 3-grams & \small 4-grams & \small BP & BLEU \\ -\midrule -1 & \small 84.7 & \small 62.0 & \small 47.2 & \small 36.4 & \small 0.969 & \textcolor{blue}{53.10} \\ -10 & \small 84.0 & \small 60.9 & \small 46.4 & \small 35.9 & \small 0.979 & \textcolor{red}{52.88} \\ -25 & \small 84.4 & \small 61.8 & \small 47.6 & \small 36.7 & \small 0.973 & \textcolor{blue}{53.47} \\ -50 & \small 84.8 & \small 61.2 & \small 46.6 & \small 36.2 & \small 0.971 & \textcolor{red}{52.83} \\ -100 & \small 83.5 & \small 60.1 & \small 45.7 & \small 35.3 & \small 0.972 & \textcolor{red}{51.86} \\ -\bottomrule -\end{tabular} -\end{exampleblock} -\end{frame} - - -%{\centering -%A unique opportunity to bring together researchers operating at the coal face of SMT development with leading theoreticians in the field of formal grammar induction. -%} -%\begin{unpacked_itemize} -%\item Understand the relationship between constituent labels and performance in SMT, -%\item Compare monolingual and bilingual induced grammars against parser output in terms of translation quality, -%\item Produce a large scale implementation of the label induction algorithms, -%\end{unpacked_itemize} -%\begin{unpacked_itemize} -%\item \alert{Learn language-pair dependent structure that produces translation performance gains across all language pairs,} -%\item \alert{Initiate a research program that redirects the SMT research community back to language neutral unsupervised systems.} -%\end{unpacked_itemize} - - -\begin{frame}[t]{Summary} -\begin{itemize} -\item Scientific Merit: - \begin{itemize} - \item A systematic comparison of existing syntactive approaches to SMT. - \item An empirical study of how constituency is useful in SMT. - \item An evaluation of existing theories of grammar induction in a practical application (end-to-end evaluation). - \end{itemize} -\item Potential Impact: - \begin{itemize} - \item Better MT systems, for more languages, across a range of domains. - \item More accessible high performance translation models for researchers. % all over the world. - \end{itemize} -\item Feasibility: - \begin{itemize} - \item A great team with a wide range of both theoretical and practical experience. - %\item Incremental plan without any deal breaking dependencies. - \item Solid preparation. - \end{itemize} -\item Novelty: - \begin{itemize} - \item First attempt at large scale unsupervised synchronous grammar induction. -% \item First study seeking to compare and understand the impact of synchronous structure on translation performance. - 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-\mode -{ - \usetheme{Boadilla} - \setbeamercovered{transparent}} - -\usepackage[english]{babel} -\usepackage{times} - -\usepackage{xcolor} -\usepackage{colortbl} -%\usepackage{subfigure} - -%% for tables -\newcommand{\mc}{\multicolumn} -\newcommand{\lab}[1]{\multicolumn{1}{c}{#1}} -\newcommand{\ind}[1]{{\fboxsep1pt\raisebox{-.5ex}{\fbox{{\tiny #1}}}}} -\newcommand{\IND}[1]{{\fboxsep1pt\raisebox{0ex}{\fbox{{\small #1}}}}} -\newcommand\production[2]{\ensuremath{\langle\mbox{#1}, \mbox{#2}\rangle}} - -%% markup -\newcommand{\buffer}[1]{{\color{blue}\textbf{#1}}} -\newcommand{\pred}[1]{\code{#1}} - -%% colors -\newcommand{\textred}[1]{\alert{#1}} -\newcommand{\textblue}[1]{\buffer{#1}} -\definecolor{tablecolor}{cmyk}{0,0.3,0.3,0} -\newcommand{\keytab}[1]{\mc{1}{>{\columncolor{tablecolor}}d}{#1}} - -% rules -\newcommand{\psr}[2]{#1 $\rightarrow \langle $ #2 $\rangle$} - -\newenvironment{unpacked_itemize}{ -\begin{itemize} - \setlength{\itemsep}{10pt} - \setlength{\parskip}{0pt} - \setlength{\parsep}{0pt} -}{\end{itemize}} - -\newcommand{\condon}{\hspace{0pt} | \hspace{1pt}} -\definecolor{darkblue}{rgb}{0,0,0.6} -\newcommand{\blueexample}[1]{\textcolor{darkblue}{\rm #1}} - -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -\newcommand{\ws}{\ensuremath{\vec{w}}} -\newcommand{\pu}{\ensuremath{P_0}} -\newcommand{\bx}{\mathbf{x}} -\newcommand{\bz}{\mathbf{z}} -\newcommand{\bd}{\mathbf{d}} -\newcommand{\by}{\mathbf{y}} -\newcommand\bleu{${B{\scriptstyle LEU}}$} - - -\title{Clustering of phrases and contexts} -\author{Trevor Cohn} -\date{\today} - -\begin{document} - -\begin{frame}[t]{Motivation} -%\vspace{1.0cm} -\begin{exampleblock}{Distributional Hypothesis} -\begin{quote} -\emph{Words that occur in the same contexts tend to have similar meanings} -\end{quote} -\hfill (Zellig Harris, 1954) -\end{exampleblock} - -\vspace{3ex} - -We will leverage this in a translation setting: -\begin{itemize} - \item Use the contexts to \alert{cluster} translation units into groups - \item Units in the same group expected to be semantically and syntactically similar - \item Then use these cluster labels to guide translation - \begin{itemize} - \item lexical selection: translating ambiguous source word/s - \item reordering: consistent syntactic patterns of reordering - \end{itemize} -\end{itemize} -\end{frame} - -\begin{frame}[t]{Monolingual Example} -Task: cluster words into their parts-of-speech. \\ - -\vspace{1ex} -Illustrate by starting with the word `deal' (noun or verb): - -\only<1>{\includegraphics[width=\columnwidth]{deal_first.pdf} \\ Step 1: Find contexts for `deal'} -\only<2->{\includegraphics[width=\columnwidth]{deal.pdf} \\ Step 2: Find other words which occur in these contexts} -%\only<3>{\includegraphics[width=\columnwidth]{deal_more.pdf} \\ \ldots continue to expand} - -\only<3>{ -\vspace{1ex} -Notice that the instances of deal can be split into two connected sub-graphs: -\begin{itemize} - \item noun: the left two contexts ``a \ldots with'' and ``a \ldots that'' - \item verb: the right two contexts ``to \ldots with'' and ``not \ldots with'' - \item neighbouring words of these contexts share the same PoS -\end{itemize} -} - -\end{frame} - -\begin{frame}[t]{More Formally} - -Construct a bipartite graph -\begin{itemize} - \item Nodes on the top layer denote word types (bilingual phrase pairs) - \item Nodes on the bottom layer denote context types (monlingual/bilingual words) - \item Edges connect words and their contexts -\end{itemize} - -\includegraphics[width=\columnwidth]{bipartite.pdf} - -\end{frame} - -\begin{frame}[t]{Clustering} - -Task is to cluster the graph into sub-graphs. Nodes in the sub-graphs should be -\begin{itemize} -\item strongly connected to one another -\item weakly connected to nodes outside the sub-graph -\item could formulate as either \emph{hard} or \emph{soft} clustering -\end{itemize} -Choose \alert{soft clustering} to allow for syntactic and semantic ambiguity - -\centering -\includegraphics[width=0.7\columnwidth]{bipartite_lda.pdf} - -\end{frame} - -\begin{frame}[t]{Latent Dirichlet Allocation (LDA)} - -LDA is a generative model which treats documents as bags of words -\begin{itemize} - \item each word is assign a \alert{topic} (cluster tag) - \item words are generated from a topic-specific multinomial - \item topics are \alert{tied} across a document using a Dirichlet prior - \item $\alpha < 1$ biases towards \alert{sparse} distributions, i.e., topic reuse - \item inferred $\theta_d$ describes a document and $\phi_t$ describes a topic -\end{itemize} - -\vspace{-3ex} -\includegraphics[scale=0.55]{lda.pdf} - -\end{frame} - -\begin{frame}[t]{LDA over Contexts} - -Generative story: -\begin{itemize} - \item for each word type $w$ - \item for each of the $L$ contexts - \item first we draw a topic $t$, then generate the context $\vec{c}$ given the topic - \item the Dirichlet prior ties the topics for each $w$ - \item we're primarily interested in the learnt $\theta$ values -\end{itemize} - -\includegraphics[scale=0.4]{context_lda.pdf} - -\end{frame} - -\end{document} diff --git a/report/intro_slides/treebanks.tex b/report/intro_slides/treebanks.tex deleted file mode 100644 index ed416031..00000000 --- a/report/intro_slides/treebanks.tex +++ /dev/null @@ -1,11 +0,0 @@ -\begin{table} - \begin{tabular}{l|rrr} - \hline - Language & Words & Domain & Source \\ \hline - Arabic & 300K (1M planned) & News & AFP newswire \\ - Chinese & 0.5M & Broadcasting news & Xinhua newswire, Sinorama and HK news \\ - English & 4.5M& Financial news & Wall Street Journal \\ - Korean & 54K & Military & Military language training manuals \\ \hline - \end{tabular} - \caption{Major treebanks: data size and domain \label{table_treebanks_size}} -\end{table} diff --git a/report/intro_slides/trevor.jpg b/report/intro_slides/trevor.jpg deleted file mode 100644 index ddee5c4a..00000000 Binary files a/report/intro_slides/trevor.jpg and /dev/null differ diff --git a/report/intro_slides/urdu-25hp.graffle b/report/intro_slides/urdu-25hp.graffle deleted file mode 100644 index efd1761b..00000000 --- a/report/intro_slides/urdu-25hp.graffle +++ /dev/null @@ -1,1053 +0,0 @@ - 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-%% sloppy linebreaks -%\sloppy - -%% no extra spacing after dots -%\frenchspacing - -\makeatletter -\setlength{\columnsep}{3mm} % this one's nasty!!! - -%\setlength{\topmargin}{0in} -%\setlength{\headheight}{0in} -%\setlength{\headsep}{-0.2in} -\setlength{\textheight}{10.0in} -%\setlength{\oddsidemargin}{0in} -%\setlength{\textwidth}{6.5in} -\setlength\titlebox{1.0in} -\renewcommand{\baselinestretch}{0.965} -\setlength{\textfloatsep}{3mm} -\setlength{\floatsep}{1.5mm} - - -\title{Models of Synchronous Grammar Induction for SMT} -\author{ - Phil Blunsom\\ - %\vspace{6pt} - Phil.Blunsom@comlab.ox.ac.uk\\ -% {\rm $^*$Computing Laboratory}\\ - University of Oxford\\ -% \And -% Alex Clark\\ -% %\vspace{6pt} -% alexc@cs.rhul.ac.uk\\ -%% {\rm $^\textrm{\textdagger}$Department of Computer Science}\\ -% Royal Holloway University -% \And -% Trevor Cohn\\ -% %\vspace{6pt} -% T.Cohn@dcs.shef.ac.uk\\ -%% {\rm $^\textrm{\textdagger}$Department of Computer Science}\\ -% University of Shefield -%\\ -% \AND -% Chris Dyer\\ -% %\vspace{6pt} -% redpony@umd.edu\\ -%% {\rm $^\textrm{\textdagger}$Department of Computer Science}\\ -% University of Maryland -% \And -% Adam Lopez\\ -% %\vspace{6pt} -% alopez@inf.ed.ac.uk\\ -%% {\rm $^\textrm{\textdagger}$Department of Computer Science}\\ -% University of Edinburgh -} - -\begin{document} -\maketitle - -%\begin{abstract} -%Synchronous grammar transducers have made a big impact in the field of machine translation in recent years. -%However, current techniques for acquiring translation grammars are either overly simplistic or else too heavily reliant on the availability of high-quality statistical parsers. -%We propose the development of algorithms for large-scale unsupervised synchronous grammar induction. -%Using advanced clustering techniques from machine learning we aim to induce grammars which use a rich set of non-terminals, %, in contrast to many existing approaches which have only one. -%thereby producing high quality translation models for language pairs solely using a parallel corpus. %, without relying on treebank parsers. -%\end{abstract} - -%%Research into statistical machine translation has changed dramatically in recent years with the introduction of grammar-based transducers (e.g., Chang's Hiero and USC/ISI's syntax-based system). -%A critical component of synchronous grammar translation models is their \emph{grammar} which encodes translational equivalence and licenses reordering between tokens in the source and target languages. -%There is considerable scope for improving beyond current techniques for automatically acquiring synchronous grammars from bilingual corpora, which seek to find either extremely simple grammars with only one non-terminal or else rely on treebank-trained parsers. -%The simple grammars are incapable of representing constituency information, while the richer grammars limit the systems' portability to new target languages while enforcing a restrictive notion of linguistic constituency. -%Instead we propose to develop an unsupervised method for large-scale unsupervised synchronous grammar induction using multiple non-terminal symbols to represent contextual information. -%In such a way we can harness the benefits of a richer grammar without the limiting data requirements or linguistic constraints. - -The last decade of research in Statistical Machine Translation (SMT) has seen rapid progress. %with small scale research systems maturing into large commercial products and ubiquitous online tools. %\footnote{e.g., translate.google.com, www.systran.co.uk, www.languageweaver.com} -Unfortunately these successes have not been uniform; -%current state-of-the-art translation output varies markedly in quality depending on the languages being translated. -%Those language pairs that are -closely related language pairs -%(e.g., English and French) -can be translated with a high degree of precision, while for distant pairs -%(e.g., English and Chinese) -the result is far from acceptable. -%It is tempting to argue that SMT's current limitations can be overcome simply by increasing the amount of data on which the systems are trained. -%However, large scale evaluation campaigns for Chinese~$\rightarrow$~English translation have not yielded the expected gains despite the increasing size of the models. -%While many researchers are tackling these issues, their proposed solutions are limited by focusing on more expressive models of translation rather than addressing the issue of how, and what, translation units are learnt a priori. - -Models which have been most successful for translating between structurally divergent language pairs have been based on synchronous grammars. -%However these successes have been tempered by a reliance on high quality monolingual parse trees on the output side of the translation model, severely restricting the applicability of such models to the case of translating into English. -A critical component of these translation models is their \emph{grammar} which encodes translational equivalence and licenses reordering between tokens in the source and target languages. -There is considerable scope for improving beyond current techniques for automatically acquiring synchronous grammars from bilingual corpora, which seek to find either extremely simple grammars with only one non-terminal or else rely on treebank-trained parsers. -The simple grammars are incapable of representing the substitutability of a constituent, while the richer grammars limit the systems' portability to new target languages (effectively limiting us to translating into/out of English) while enforcing a restrictive notion of linguistic constituency (Figure \ref{fig:models}). -%A further, but more subtle, limitation of these models is the assumption that the particular brand of linguistic structure assigned by a parser (usually a form of phrase structure grammar learnt from the Penn. Treebank) is predominantly isomorphic to that of the input language; an assumption which is rarely true for distantly related language pairs (or even closely related ones: Figure \ref{fig:models}). - -Clearly there is a need for research into the unsupervised induction of synchronous grammar based translation models. -%Previous research has focussed on structured learning approaches requiring costly global inference over translation pair derivations, limiting the ability of these models to be scaled to large datasets. -We propose the pragmatic approach of embracing existing algorithms for inducing unlabelled SCFGs (e.g. the popular Hiero model), and then using state-of-the-art hierarchical non-parametric Bayesian models to independently learn syntactic classes for translation rules in the grammar. - - -The agenda of the workshop will address two goals: (1) to implement and systematically investigate the performance of current synchronous grammar based SMT systems, focusing on the role of constituency and syntactic classes in informing translation structure; (2) to develop scalable unsupervised algorithms for assigning labels to translation rules in synchronous grammars. -These algorithms will be implemented within the {\em Joshua} decoder with the intention of providing an open source implementation of the existing and proposed synchronous grammar SMT systems. - -\paragraph{1) Systematic comparison of synchronous grammar based SMT} -Firstly we will extend the Joshua decoder to handle a range of the currently proposed synchronous grammar based SMT models. -Through experimentation on a range of parallel corpora (small and large, hi and low density languages), we will systematically explore the question of what the most effective models of synchronous syntax for SMT are. -%Previous work has assumed a linguistic motivation, but there is a compelling argument that a more appropriate representation may be one which specifically addresses the divergence between a given language pair (Figure~\ref{fig:models}). -%Such a grammar might simply encode the number of tokens in the constituent being generated, the number of reordering operations on the path from the root to that constituent, or whether a constituent prefers to reorder in a specific direction. - -\paragraph{2) Unsupervised learning of labelled synchronous grammars} -The second goal will be to apply unsupervised Bayesian techniques, such as Latent Dirichlet Allocation (LDA) and hierarchical non-parametric models (HDPs, HPYPs), to the task of assigning equivalence classes to phrase translations. -Inspired by work in monolingual PCFG learning, we will investigate generative models which describe the production of phrase translations in terms of sequences of tokens (or word classes) and their observed contexts. - -We have put together an enviable superset of faculty and graduate students from which the senior members of the workshop will be drawn: Joy Ying Zhang (CMU), Trevor Cohn (Sheffield), Alex Clark (RHUL), Chris Dyer (UMD), Adam Lopez (Edinburgh), Yang Liu (CAS), Zhifei Li (JHU) and Andreas Zollmann (CMU). - -The success of the workshop will impact widely on both the machine translation community, and the field of grammar induction. -By investigating our stated goals in the context of a CLSP workshop we will provide a deep understanding of synchronous grammar based SMT; both generating interest and furthering research into widely applicable unsupervised techniques for synchronous grammar induction. -Such techniques promise to bring high performance SMT models, only currently applicable to working with English, to the full range of languages of the world. -In addition we will provide a benchmark implementation of synchronous grammar based SMT models ready for wide adoption within the SMT research community. - -\begin{figure} -% \subfigure[Formal syntax]{\includegraphics[scale=0.2]{JeNeVeuxPasTravailler-Hiero.pdf}} - \subfigure[Unsupervised syntax]{\includegraphics[scale=0.36]{JeNeVeuxPasTravailler-hiero-labelled.pdf}} - \subfigure[Treebank syntax]{\includegraphics[scale=0.36]{JeNeVeuxPasTravailler-tsg.pdf}} -\caption{What is the best syntactic structure for SMT?} -\label{fig:models} -\end{figure} -\end{document} diff --git a/report/intro_slides/wsj23_example.pdf b/report/intro_slides/wsj23_example.pdf deleted file mode 100644 index 860fc83d..00000000 Binary files a/report/intro_slides/wsj23_example.pdf and /dev/null differ diff --git a/report/intro_slides/ziyuan.pdf b/report/intro_slides/ziyuan.pdf deleted file mode 100644 index 43c9efd2..00000000 Binary files a/report/intro_slides/ziyuan.pdf and /dev/null differ diff --git a/report/introduction.tex b/report/introduction.tex deleted file mode 100644 index 41d1e81b..00000000 --- a/report/introduction.tex +++ /dev/null @@ -1,124 +0,0 @@ -\chapter{Introduction} - -Automatically generating high quality translations for foreign texts remains a central challenge for natural language processing research. -Recent advances in statistical machine translation (SMT) has enabled these technologies to move out of research labs an become viable commercial products and useful online tools. \footnote{e.g., translate.google.com, www.systran.co.uk, www.languageweaver.com} -However these successes have not been uniform; -current state-of-the-art translation output varies markedly in quality depending on the languages being translated. -Those language pairs that are closely related language pairs (e.g., English and French) can be translated with high quality, while for distant pairs (e.g., English and Chinese) the result tends to be much lower quality. -It is tempting to argue that SMT's current limitations can be overcome simply by increasing the amount of data on which the systems are trained. -However, large scale evaluation campaigns for Chinese~$\rightarrow$~English translation, such as the DARPA GALE program, have not yielded high quality translation despite providing hundreds of millions of words worth of training data. - -\begin{figure}[t] - \centering \includegraphics[scale=0.55]{urdu_example_translation.pdf} -\caption{An example Urdu $\rightarrow$ English translation show outputs from both a state-of-the-art Hiero translation model, and Google's translation service.} -\label{fig:intro_urdu_example} -\end{figure} -Figure \ref{fig:intro_urdu_example} shows the current state-of-the-art for translating an Urdu sentence into English. -While a considerable portion of the content of the input Urdu sentence is translated, the end result is still far from being acceptable for an end user. -%\begin{figure} -% \centering \includegraphics[scale=1.3]{intro_slides/WhoWroteThisLetter.pdf} -%\caption{The level of structural divergence varies depending on the language pair in question.} -%\label{fig:intro_translation_divergence} -%\end{figure} -Many of the issues faced by SMT systems can be attributed to structural divergence between the languages being translated. -While many researchers are tackling these issues, most proposed solutions are limited by focusing on more expressive models of translation rather than addressing the issue of how, and what, translation units are learnt a priori. - - -\begin{table}[t] -\centering - \begin{tabular}{l|rr} - \hline - Language & Words & Domain \\ \hline - English & 4.5M& Financial news \\ - Chinese & 0.5M & Broadcasting news \\ - Arabic & 300K (1M planned) & News \\ - Korean & 54K & Military \\ \hline - \end{tabular} -\caption{Major treebanks: data size and domain.} -\label{tab:intro_treebanks} -\end{table} -%\begin{figure} -% \centering \includegraphics[scale=0.3]{intro_slides/resource_matrix.pdf} -%\caption{A matrix of the number of parrallel words available for various language pairs.} -%\label{fig:intro_parallel_words_matrix} -%\end{figure} - -\begin{figure}[t] - \centering - \subfigure{\includegraphics[scale=0.5]{intro_slides/JeVeuxTravailler-Hiero.pdf}} - \subfigure{\includegraphics[scale=0.5]{intro_slides/JeNeVeuxPasTravailler-Hiero.pdf}} -\caption{Example derivations using the Hiero grammar extraction heuristics \cite{chiang07hierarchical}.} -\label{fig:intro_hiero} -\end{figure} - -\begin{figure}[t] - \centering - \subfigure{\includegraphics[scale=0.5]{intro_slides/JeNeVeuxPasTravailler-tsg.pdf}} - \subfigure{\includegraphics[scale=0.5]{intro_slides/JeVeuxTravailler-tsg.pdf}} -\caption{Example derivations for a Tree Substitution Grammar derived from a parallel corpus parsed with a supervised parser.} -\label{fig:intro_tsg} -\end{figure} - -Models which have been most successful for translating between structurally divergent language pairs have been based on synchronous grammars. -A critical component of these translation models is their {\emph grammar} which encodes translational equivalence and licenses reordering between tokens in the source and target languages. -There is considerable scope for improving beyond current techniques for automatically acquiring synchronous grammars from bilingual corpora, which seek to find either extremely simple grammars with only one non-terminal or else rely on treebank-trained parsers. -The advantage of using a simple grammar is that no extra annotated linguistic resources are required beyond the parallel corpus. -However these simple grammars are incapable of representing the substitutability of a constituent. -Figure \ref{fig:intro_hiero} displays a synchronous derivation in such a simple grammar. -Richer grammars induced from a parallel corpus annotated with syntax trees overcome the limitations of the simple grammars and provide a far more powerful representation of language structure. -Figure \ref{fig:intro_tsg} shows a synchronous derivation in for a grammar extracted parallel corpus parsed on the English side. -The limitation of this approach is that the reliance on supervised parses restricts the systems' portability to new target languages (effectively limiting us to translating into/out of English) while enforcing a restrictive notion of linguistic constituency. -Figure \ref{fig:intro_parallel_words_matrix} shows the number of words in the treebanks available for the most well resourced languages. -As the performance of supervised parsers is heavily dependent on the amount of training data available, clearly we can expect poorer results when building translation models based upon then for languages other than English. -A further, but more subtle, limitation of these models is the assumption that the particular brand of linguistic structure assigned by a parser (usually a form of phrase structure grammar learnt from the Penn. Treebank) is predominantly isomorphic to that of the input language; an assumption which is rarely true for distantly related language pairs, or even closely related ones. - - - -Clearly there is a need for research into the unsupervised induction of synchronous grammar based translation models. -Previous research has focussed on structured learning approaches requiring costly global inference over translation pair derivations, limiting the ability of these models to be scaled to large datasets \cite{blunsom09bscfg}. -In this workshop we adopted a pragmatic approach of embracing existing algorithms for inducing unlabelled SCFGs (e.g. the popular Hiero model \cite{chiang07hierarchical}), and then used state-of-the-art probabilistic models to independently learn syntactic classes for translation rules in the grammar. -We structured the workshop into three parallel but interdependent streams: - -\begin{figure} - \centering - \includegraphics[scale=0.5]{intro_slides/JeNeVeuxPasTravailler-hiero-labelled.pdf} -\caption{Example derivation using the Hiero grammar extraction heuristics where non-terminals have been clustered into unsupervised syntactic categories denoted by $X?$.} -\label{fig:intro_labelled_hiero} -\end{figure} - - -\paragraph{1) Unsupervised induction of labelled SCFGs} -Inspired by work in monolingual PCFG learning, we have investigated generative models which describe the production of phrase translations in terms of sequences of tokens (or word classes) and their observed contexts. -We simplify the grammar induction problem to first clustering monolingual phrases based upon their distribution over contexts (preceding and following words), and then intersecting these labelled phrases with the Hiero \cite{chiang07hierarchical} SCFG rule extraction heuristics. -The end result are grammars that produce derivations like that in Figure \ref{fig:intro_labelled_hiero}, where the labels are the unsupervised clusters induced by our context based induction algorithm. - -We explored two approaches to the clustering of phrases. -The first was inspired by research in Topic Modelling, in particular Latent Dirichlet Allocation (LDA). -We formulated a model in which each phrase type maintains a distribution over labels, and each context a phrase appears in is generated by first choosing a label, and then generating the context from this labels distribution over contexts. -We extended the basic LDA model to incorporate hierarchical Pitman Yor distributions on the two generating components of the model. -In the second approach we optimised the same model as describe above, but in instead of using non-parametric Bayesian approach to encouraging sparsity in the model, we used the direct Posterior Regularisation technique of \cite{someone}. - -The labelled SCFGs produced by these algorithms generate a subset of the translations licensed by the original Hiero grammars. -While we hope that this restriction guides the model to more acceptable translations, with the inevitable noise present in all automatically induced translation models it is advantageous to allow our models to degrade gracefully to less restrictive grammars. -As such we also explored hierarchical cascades of grammars, each of which was induced with a different number of labels, allowing the translation model to switch between these while incurring a penalty for doing so. - -This work on inducing labels for SCFGs formed the core component of the workshop and the base for the following work exploiting these labellings. -By the conclusion of the workshop we were able to demonstrate that applying these induction techniques leads to improved translations for both Chinese$\rightarrow$English and Urdu$\rightarrow$ translation systems. -Chapter \ref{chap:grammar_induction} describes this work. - -\paragraph{2) Decoding with labelled SCFGs} -The second major component of the workshop involved the investigation of improved decoding algorithms for the type of labelled SCFG produced by our induction methods. -Decoding complexity scales quadratically with the number of labels in the grammar. -As such inducing grammars with more than one label significantly increases the time and resources required for decoding. -We explored a number of avenues for reducing this computational burden, including the early pruning items from the search space before language model integration, and coarse-to-fine techniques in which decoding is performed with grammars with progressively more labels and pruning at each step. -We were able to show that each of these techniques could lead to faster decoding without compromising translations performance. -Chapter \ref{chap:decoding} describes this work. - -\paragraph{3) Discriminative training labelled SCFG translation models} -The third stream of the workshop focussed on implementing discriminative training algorithms for the labelled SCFG translation models produced by our unsupervised grammar induction algorithms. -Though the existing MERT \cite{och02mert} training algorithm is directly applicable to these grammars, it doesn't allow us to optimise models with large numbers of fine grained features extracted from the labels we've induced. -In order to maximise the benefit from our induced grammars we explored and implemented discriminative training algorithms capable of handling thousands, rather than tens, of features. -The algorithms we explored were Maximum Expected Bleu \cite{smith,li} and MIRA \cite{chiang}. -Chapter \ref{chap:training} describes this work. - -The remainder of this introductory chapter provides a formal definition of SCFGs and describes the language pairs that we experimented with. diff --git a/report/morphology/al_orig.pdf b/report/morphology/al_orig.pdf deleted file mode 100644 index f3fdb2ad..00000000 Binary files a/report/morphology/al_orig.pdf and /dev/null differ diff --git a/report/morphology/al_segm.pdf b/report/morphology/al_segm.pdf deleted file mode 100644 index 46a361d3..00000000 Binary files a/report/morphology/al_segm.pdf and /dev/null differ diff --git a/report/morphology/alignments.svg b/report/morphology/alignments.svg deleted file mode 100644 index 5e5805b6..00000000 --- a/report/morphology/alignments.svg +++ /dev/null @@ -1,197 +0,0 @@ - - - - - - - - - - - - - - image/svg+xml - - - - - - - daaraan mag niets veranderd worden . les modifications n' ont pas lieu d' être . - - - - - - daar+ +aan mag niet +s veranderd word+ +en . les modifi+ +cation +s n' ont pas lieu d' être . - - - - - - - - - - - - - diff --git a/report/morphology/morphology.tex b/report/morphology/morphology.tex deleted file mode 100644 index 80ce9fe2..00000000 --- a/report/morphology/morphology.tex +++ /dev/null @@ -1,348 +0,0 @@ -\newcommand{\gloss}[1]{\glossa{(#1)}}%\begin{small}\textit{(#1)}\end{small}} -\newcommand{\glossa}[1]{\begin{small}\textit{#1}\end{small}} -\newcommand{\pemph}[1]{\textbf{#1}} -\newcommand{\mmsz}{0.4\textwidth} -\newcommand{\mmultirow}[2]{\multirow{#1}{\mmsz}{#2}} - -\chapter{Inducing Morphological Structure} - -In this chapter, we evaluate the application of our grammar induction method to the problem of translating at the morphology level. - -\section{Introduction} -Mainstream SMT research mostly ignores morphological variation, treating translation as a mapping of words and phrases from a source to a target language without taking cognisance of word-internal structure. -This approach has worked reasonably well for various languages, but is ill-suited for language pairs with substantial morphological divergence, e.g. Turkish and English. - -Morphological variation is a source of sparseness in the training that can make it hard or impossible to produce correct translations of word forms not observed during training, or observed only rarely. -The sparseness problem can of course be mitigated by using ever larger sets of training data, but for anything short of an infinite parallel corpus, a language with relatively expressive morphology should succeed in producing word forms that simply never appear in the corpus. -This is especially true for languages with complex morphology like Turkish, Finnish and Hungarian, where there is a proliferation of word forms. - -Ideally, we would like to leverage the words observed in the training data to generate differently inflected forms of them. -For example, the correct conjugation of the French verb for ``(we)~hear'' could be generated as illustrated below, where boldface and underlining mark the origins of the relevant word segments: - -\begin{figure}[h] -%\label{fig:inflection} -\centering - \begin{tabular}{rlcll} - \multicolumn{2}{c}{\textbf{\textit{Observed}}} & & \multicolumn{2}{c}{\textbf{\textit{Generated (not observed)}}} \\[5pt] - \gloss{I hear} & j'\textbf{entend}s - & \multirow{2}{*}{$\Longrightarrow$} - & \multirow{2}{*}{nous \textbf{entend}\underline{ons}} - & \multirow{2}{*}{\gloss{we hear}} \\ - \gloss{we reply} & nous r\'{e}pond\underline{ons} & & & - \end{tabular} -%\caption{Learning from morphemes: Boldface and underlining trace the elements used to form the unobserved word. English translations are given in parentheses.} -\end{figure} - -In general, our aim here is to identify morphemes in the observed words and combine them correctly to generate novel word forms. -To achieve this, we require rules for how morphemes may combine. -Such rules could be hand-crafted for a particular language, but in keeping with the spirit of statistical MT, we strive toward language independent solutions and would rather induce rules from data. -A SCFG could be suitable for expressing such rules, so how about we use the grammar induction methods discussed earlier to obtain one that is capable of translating morphemes. -In particular, the plan is to have a single grammar deal with morpheme combination (i.e. word formation) as well as sentence formation. -This is the central idea for this chapter and is developed further in the next section. - -\paragraph{Work this in somewhere} -Morphology has received attention in SMT research before, with reasonable success both - when the source language has richer morphology than the target language \citep{Yang2006,Dyer2008}, - and vice versa \citep{someone,Yeniterzi2010} . -To our knowledge, Dyer08 is the only other case where morphology has been targeted in the context of a translation system that uses SCFG for transduction. - -In the monolingual setting, morphology has been modelled with -rule-based finite-state automata \citep{someone}, -unsupervised methods \citep{Creutz2006,Goldsmith2001}, - .. lookup those leads from workshop feedback]. Highlight what is novel/unique about our approach. - -\section{Motivation for a Labelled Grammar} -We use the Hiero-grammar with its single non-terminal category, X, as a starting point and imagine that we induce it from a corpus that has been segmented into morphemes. -For the moment, we ignore the fact that this grammar is synchronous. -Observe that a context-free grammar can be employed to generate words from morphemes, as shown by the grammar fragment and derivation of ``enabled'' in Figure \ref{fig:m_motivation_x}. - -Yet the same grammar fragment also licenses the production of nonsense, such as ``enablely''. -This is because this grammar does not enforce proper restrictions on morpheme attachment, allowing a string like ``+ly address'' to attach to ``enable+'' as a `suffix'. - -We use the `+' character to mark morpheme boundaries. -Apart from being a a display device, it also creates a distinction in the vocabulary if some token exists -both as a morpheme and a word in its own right. -But it is insufficient for enforcing proper attachment, even if the grammar were aware of the marker's meaning. - -\subfigcapskip=15pt -\begin{figure}[h] - \centering - \subfigure[Non-sensical words can be produced when using a single non-terminal category.]{\label{fig:m_motivation_x} - \begin{tabular}{rcl} - \begin{minipage}{0.3\textwidth} - \begin{tabular}{lcl} - X & $\rightarrow$ & en+ +able+ X \\ - X & $\rightarrow$ & +d \\ - \textit{X} & $\rightarrow$ & \textit{+ly address} \\ - \end{tabular} - \end{minipage} - & - \begin{minipage}{0.3\textwidth} - \includegraphics[scale=1]{morphology/treelet_good} - \end{minipage} - & - \begin{minipage}{0.3\textwidth} - \includegraphics[scale=1]{morphology/treelet_bad} - \end{minipage} - \\ - \end{tabular} - } - - \subfigure[Constraining the grammar with labelled rules can avoid the problem.]{\label{fig:m_motivation_labelled} - \begin{tabular}{rl} - \begin{minipage}{0.4\textwidth} - \begin{tabular}{lcl} - X & $\rightarrow$ & en+ +able+ \textbf{X3} \\ - \textbf{X3} & $\rightarrow$ & +d \\ - X & $\rightarrow$ & +ly address \\ - \end{tabular} - \end{minipage} - & - \begin{minipage}{0.3\textwidth} - \includegraphics[scale=1]{morphology/treelet_good_label} - \end{minipage} - \\[10pt] - \end{tabular} - } - \caption{Grammar fragments and possible derivations they allow when using a single category (top) vs. multiple categories (bottom).} - \label{fig:m_motivation} -\end{figure} -\subfigcapskip=10pt - -To solve the problem, we wish to constrain the grammar by using more refined non-terminal categories. -Specifically, we do not want the word-forming and sentence-forming rules of the grammar to mix. -Thus we propose to use a set of labelled categories for word-formation, disjoint from X. -With the modified grammar fragment shown in Figure \ref{fig:m_motivation_labelled}, the non-sensical word can no longer be produced. - -These examples only serve to illustrate word formation in the monolingual case. -Of course, we are actually operating in a bilingual situation and using synchronous CFGs. -Thus, another merit of this approach is that it can capture morpheme reordering in a natural way. (Example). - -\section{Morpheme Clustering and Labelling} -By no mere coincidence, we have a suitable source of the aforementioned kind of labelled grammar rules in the form of the clustering method described in chapter \ref{chap:np_clustering}. -We will use it to cluster morphemes depending on their context within words. -To this end we use the normal phrase extraction heuristics on a corpus that has been segmented into morphemes. -Thus in the terminology introduced earlier in this report, a phrase $\mathbf{p}$ and its context $\mathbf{c}$ are both sequences of morphemes, as illustrated below. -Importantly, we only perform the clustering on phrases not containing word boundaries, since we are specifically after rules of word formation. - -\begin{figure}[h] -\begin{tabular}{ll} -\textit{Original sentence:}\footnote{Gloss: \gloss{changes have no place to be}} & les modifications n' ont pas lieu d' \^{e}tre \\[3pt] -\textit{Segmented sentence:} & - $\underbrace{\textrm{les}}_{c_{-1}} \; - \underbrace{\textrm{modifi+}}_{\mathbf{p}} \; - \underbrace{\textrm{+cation+}}_{c_{+1}}$ \; +s n' ont pas lieu d' \^{e}tre \\[8pt] - \multicolumn{1}{r}{$\Rightarrow$} - & $\mathbf{p}= (\textrm{modifi+}),$ \\ - & $\mathbf{c} = (c_{-1},c_{+1}) = (\textrm{les, +cation+})$ -\end{tabular} -\end{figure} - -The underlying assumption made by applying this clustering method is that a morpheme's context is indicative of its substitutability. -The previous example is an instance of noun derivation from a verb stem. -In order to form other nouns by this mechanism, different verb stems need to be substituted in place of ``modifi+''. -This can be achieved if the appropriate morphemes occurring in this context are clustered together under the same label, say, $z=15$: - -\begin{center} -\begin{tabular}{ccl|ccl} -les & modifi+ & +cation+ & les & justifi+ & +cation+ \\ - & X15 & & & X15 & \\ -\end{tabular} -\end{center} - -Morphemes in the training corpus are labelled in this way, based on the categories induced by clustering. -This still leaves many spans in the corpus unlabelled, in particular those that contain word boundaries. -During grammar extraction, these spans give rise to the sentence-forming X-rules, whilst the labelled spans yield the word-forming labelled rules, as detailled previously. - -\section{Experimental Setup} -The ideas expressed above need to be verified empirically. -The most direct approach was to do this somewhat isolated from the other workshop experiments. -In other words, we used a Hiero-grammar as the starting point and used the clustering to learn morpheme combination rules only. -We did not also apply it to words and phrases, although that was starting to show the improved BLEU scores reported elsewhere in this document. - -We chose Dutch and French as a test language pair, since 1) they both have a fair amount of interesting inflection and 2) it was the most suitable language pair from amongst those for which suitable training data was prepared before the workshop. - -\subsection{System Description} - -\paragraph{Data} -We filtered the training corpus down to the first 100k sentence pairs that contain at most 40 words per sentence. -The word limit was imposed because the actual number of tokens in a sentence will be higher once it is segmented into morphemes. -This was a time-saving shortcut on various fronts: It restricts the size of the extracted grammars and therefore the decoding time too, and, more importantly, allowed us to obtain the new word alignments and language model in a reasonable amount of time. -It also makes the alignment task slightly less error-prone, although this remains problematic and is discussed in section \ref{sec:m_analysis}. - -\paragraph{Segmentation} -For word segmentation, we used the unsupervised Morfessor Categories-MAP algorithm \citep{Creutz2007}, which is based on a HMM. -It induces a word segmentation model from a monolingual corpus, where a word consists of one or more stem morphemes with zero or more prefixes and/or suffixes, each marked as such. -Since we weren't interested in how well Morfessor can segment words it did not observe during its training stage, we trained a segmentation model on the complete training, development and test data that will be used by the translation system. -We did not make use of the induced morpheme categories (prefix, stem, suffix), but simply applied the segmentation models to split the training, development and test data into generic morphemes. - -The granularity of segmentation is controlled by specifying a perplexity threshold ($PPL$ in the Morfessor configuration file). -After some informal tests on a small data set, we chose $PPL_{\textrm{Dutch}}=300$ and $PPL_{\textrm{French}}=150$. -Table \ref{tbl:segmentation} summarises the effect this had on the (MT) training data. - -\begin{table}[h] - \centering - \begin{tabular}{|l|l|r|r|} - \multicolumn{2}{c}{} & \multicolumn{1}{c}{Dutch} & \multicolumn{1}{c}{French} \\ \hline - \multirow{2}{*}{Types} & words & 43611 & 35225 \\ \cline{2-4} - & morphemes & 26409 & 21962 \\ \hline - \multirow{2}{*}{Tokens} & words & 2035254 & 2180898 \\ \cline{2-4} - & morphemes & 2647203 & 2874574 \\ \hline - \end{tabular} - \caption{x}\label{tbl:segmentation} -\end{table} - -\paragraph{Grammar Induction Parameters} -We obtained two grammars for testing, one by clustering the source side and the other on the target side. -Following from other workshop results, we chose $K=25$ categories, although our setting here is rather different. -Morpheme sequences of at most $|\mathbf{p}|=10$ were obtained from the aligned, segmented corpus using the standard phrase extraction method and context was chosen as one token either side of such a sequence, i.e. $\mathbf{c}=(c_{-1},c_{+1}$. -The non-parametric model with hierarchical Pitman-Yor Process priors was run for a 1000 samples in each case and the last sample used to label morpheme sequences. -The resulting grammars each have a total of 26 non-terminal categories: the default X category plus the 25 labelled categories. - -\paragraph{Translation System} -Word alignments were trained on the segmented parallel corpus using the Berkeley Aligner \citep{Liang2006} with default settings. - -A French language model over morpheme n-grams was also required. -3-gram language models were used throughout the workshop. -But due to word segmentation, the number of tokens in the French training corpus, and therefore the average number of tokens per sentence, increased by 32\% (Table \ref{tbl:segmentation}). -We therefore opted for a 4-gram language model, since that yields, on average, three full words of context, thus corresponding to a 3-gram model on unsegmented data. - -\section{Results} - -\subsection{Intrinsic Evaluation} -In order to gain some insight into the quality of the morpheme clustering, we scrutinised cluster contents for obvious patterns. -This was done only for the case where the clustering was done on Dutch (source language), since expertise was available there but not in French. -Some of the observations are summarised in Table~\ref{tbl:m_cats}. - -\begin{table}[hbt] - \centering - \input{morphology/morphology_tblcats} - \caption{A selection of observations about the outcome of clustering morpheme sequences in the source language (Dutch). Cluster sizes ranged from X to Y.} - \label{tbl:m_cats} -\end{table} - -The quality of unsupervised clustering is generally tricky to judge. -In our case, it involves determining whether the clusters encode useful ``rules'' for morpheme combination. -There are strong indications that certain worthwhile patterns are learned and that the clustering is therefore partially successful. -To highlight some, note in Table~\ref{tbl:m_cats} that categories~4 and 6 involve a clear separation between two high-level parts of speech, and that a fine-grained distinction about Dutch nouns was learned in categories~10 and 16. - -On the other hand, there are ample examples of conflation. Sometimes there is little or no useful linguistic pattern that can be discerned. -As an example, the conflation shown for category~0 implies that both ``europe+'' and ``+s'' will receive the same label, which would give rise to the kind of unrestricted substitutability that we wanted to avoid, as explained in Figure~\ref{fig:m_motivation}. - -\subsection{Extrinsic Evaluation} -Ultimately, performance in translation is what matters. -The main question is what impact clustering has when applied to segmented training data. -The baseline system is therefore trained on the same segmented data but without the clustering, i.e. using the Hiero grammar. -For further comparison, we also include the score Hiero achieves on the same training data in its original, unsegmented form. - -Table \ref{tbl:m_bleu} gives the final BLEU scores. - -\begin{table}[htb] - \centering - \begin{tabular}{|l|c|c|c|} \hline - & \textbf{OOV} & \textbf{BLEU}(m) & \textbf{BLEU} \\ \hline - Hiero (\textbf{baseline}) & x & 20.92 & \textbf{15.57} \\ \hline - Source clustered & x & 20.63 & \textbf{15.37} \\ \hline - Target clustered & x & 20.66 & \textbf{15.42} \\ \hline - \multicolumn{3}{c}{ } \\ \hline - Hiero, original data & x & 20.55 & \textbf{15.67} \\ \hline - \end{tabular} - \caption{Results, averaged over 3 MERT runs. BLEU(m) is calculated on the segmented output (i.e. the actual output in the first three cases), whereas last column contains the final scores after recombining the output morphemes into words.} - \label{tbl:m_bleu} -\end{table} - -\subsection{Analysis} \label{sec:m_analysis} -The fact that our approach degraded translation quality as measured by BLEU can be attributed to various factors. - -The primary reason is that the word segmentation introduces (additional) errors into the bilingual token alignments. -The alignments are crucial, since they determine the phrases (morpheme sequences) that are extracted and input to the clustering and grammar extraction algorithms. -Alignment errors can therefore have a serious impact on the quality of the resulting grammar. - -As an example of the kind of errors made, observe in Figure~\ref{fig:m_alignment_error} that morphemes from unrelated source and target words can be aligned. -Although this behaviour could be useful for modelling certain agreement phenomena or where linguistic information is expressed differently by the two languages, it causes more harm than it does good. -In this case, it is not surprising that it mistakenly aligns the ending of the verb ``worden'' with that of the plural noun ``modifications'', since ``+en'' and ``+s'' are both plural forming suffixes and their alignment would be correct in many other contexts. -Likewise for the endings of ``niets'' (not a verb, though) and ``modifications''. -In general, it is also clear that the alignment of the segmented sentence pair is more complex than the unsegmented one, meaning there is more room for error. - -\begin{figure}[hb] - \centering - \subfigure[Before segmentation]{\includegraphics[scale=1]{morphology/al_orig}} - \hspace{10mm} - \subfigure[After segmentation]{\includegraphics[scale=1]{morphology/al_segm}} - \caption{Alignment errors increase under segmentation. (English: {\emph Nothing may be changed about that.})} - \label{fig:m_alignment_error} -\end{figure} - -These alignment errors affect both the baseline and clustered systems. -However, the use of a single non-terminal probably allows the baseline system to recover better from bad grammar rules, due to the unrestricted substitution it licenses. -In the clustered cases, on the other hand, the grammars are more constrained by design; there is no mechanism to recover from being constrained in the wrong way, aside from the standard glue rules. - -%Comparing only the Hiero-cases, we see that segmentation decreased BLEU ($15.67\to15.57$). -%Segmentation of both languages into morphemes has been shown to have this effect when using phrase-based SMT \citep{Virpioja2007}. -%However, we had expected an even larger decrease, and it might be that segmentation is less harmful in the context of hierarchical phrase-based translation (e.g. Hiero). - -A further factor is that BLEU, applied in the standard way, is unforgiving towards partially correct words: - A word with the correct stem and incorrect inflection gets penalised just the same as a wholly incorrect word. -Such partial improvements should increase the BLEU(m) score, Table~\ref{tbl:m_bleu}: -Segmentation does have this effect, but the unclustered baseline does best by this measure. - -Neither the unigram scores nor the percentage of dangling morphemes in the output (i.e. ones that cannot recombine into words) improved under clustering. - -On a positive note, however, clustering succeeded in correctly generating words not observed in the training, and for which the other systems failed: - -\begin{table}[h] - \begin{tabular}{llp{0.45\textwidth}} - Input: & het ivoriaanse model & \multirow{2}{*}{\gloss{the pertaining\_to\_Ivory\_Coast model}} \\ - Reference: & du mod{\`e}le \textbf{ivoirien} \\ \hline - Baseline: & du mod{\`e}le \textbf{ivoir\"{i}enne} & incorrect gender \\ - Source clustered: & du \textbf{ivoirien} mod{\`e}le & correct gender, but wrong word order \\ - \phantom{.} \\ - Input: & de antidumpingmaatregelen & \multirow{2}{*}{\gloss{the anti-dumping measures}} \\ - Reference: & des \textbf{mesures antidumping}\\ \hline - Baseline: & \textbf{anti mesures dumping} & correct morphemes, but bad order \\ - Target clustered: & les \textbf{mesures antidumping} & ...although +dumping+ is simply propagated as is from the Dutch input \\ - \end{tabular} -\end{table} - -\section{Conclusions and Future Work} -We have presented an approach to using a Hiero-type SCFG to perform translation at the morphology level. -Context-based clustering of morpheme sequences allowed grammar rules to be constrained in way that should limit the formation of non-sensical words. - -We found that clustering \textit{per se} succeeded to a large extent. -The clusters we analysed contained strong and clear patterns, learning for example a fine-grained distinction between noun gender in Dutch. - -In the context of translation, our approach managed to formulate novel words that were not observed in the training data, and this was a major part of our aim. -On the whole, however, our approach degrades translation quality. - -Although our translation results were negative, we would not completely discard the idea of using a SCFG in this way. -The main problem is that segmenting the data introduces harmful errors into the word alignments. -Bad alignments mean we're screwed from the start. \textit{Thinking out loud. Tone will be fixed later...} - -So we have to fix them. - -A further aspect is that translation at the morpheme level is not appropriate in all cases. -We really only want it to be used when confronting rare words or are called upon to create new ones. - -A logical next step will be to combine our approach using the back-off grammar work discussed elsewhere in this report. -The idea would be to train a labelled grammar on segmented data (as we have done here) but allow back-off to a grammar trained on the unsegmented data. -This would require sentences to be input to the decoder as lattices, so that there is no hard decision about whether words or morphemes are the best granularity of representation. -This would require modifying the decoding algorithm to recombine morphemes into words when appropriate and score against a language model trained on full words. - - -%Future possibilities: combine with back-off grammar work, e.g. back-off from a labelled grammar (trained on segmented data) to a Hiero grammar (trained on the unsegmented data). -%express input as a lattice. That way there's no hard decision about whether to use words or morphemes. It would also require changes to decoding: e.g. morphemes will need to be combined into words whenever appropriate and scored against a LM trained on full words. -% -%need to find better solutions to the alignment problems - - - - - - - - - - - - - diff --git a/report/morphology/morphology_tblcats.tex b/report/morphology/morphology_tblcats.tex deleted file mode 100644 index d19b18f6..00000000 --- a/report/morphology/morphology_tblcats.tex +++ /dev/null @@ -1,84 +0,0 @@ - \begin{tabular}{c|p{\mmsz}|l} - \textbf{$z$} & \textbf{Description} & \textbf{Examples} \\ - & & format: $c_{-1}$ \p\ $c_{+1}$ \gloss{translation} \\ \hline - 0 & \parbox{0.4\textwidth} - {75\% concerns the infix +s+, both as \p\ and as $c_{+1}$} & - \begin{minipage}{0.4\textwidth} - \begin{tabular}{ll} - de \pemph{europe+} +s+ & \gloss{the european+} \\ - europe+ \pemph{+s+} +e & \gloss{european} - \end{tabular} - \end{minipage} \\ \hline - - 1 & \parbox{0.4\textwidth} - {$>$85\% prefix morphemes as \p, mostly noun stems with plural forming $c_{+1}$.} & - \begin{minipage}{0.4\textwidth} - \begin{tabular}{ll} - ... \pemph{resolutie+} +s & \gloss{resolutions} \\ - ... \pemph{kilometer+} +s & \gloss{kilometres} \\ - \end{tabular} - \end{minipage} \\ \hline - - 4 & \parbox{0.4\textwidth} - {$>$99\% verb stems as \p} & - \begin{minipage}{0.4\textwidth} - \begin{tabular}{ll} - ge+ \pemph{+maakt} ... & \gloss{made} \\ - ver+ \pemph{+werpt} ...& \gloss{reject(s) [verb]} \\ - samen+ \pemph{+brengt}...& \gloss{bring together} \\ - \end{tabular} - \end{minipage} \\ \hline - - 5 & \parbox{0.4\textwidth} - {25\% \p-instances are the prefix ``ver+''. \\ - 25\% \p-instances are the domain-specific suffix ``+missie''. \\ - 14\% $c_{+1}$-instances are the adjective-deriving suffix ``+isch''.} & - \begin{minipage}{0.4\textwidth} - \begin{tabular}{ll} - ... \pemph{ver+} +slag & \gloss{report} \\ - ... \pemph{ver+} +beter & \gloss{improve} \\ - com+ \pemph{+missie} ... & \gloss{commission} \\ - ?? isch \\ - \end{tabular} - \end{minipage} \\ \hline - - 6 & \parbox{0.4\textwidth} - {$>$99\% adjective stems, followed by a marker for definiteness.} & - \begin{minipage}{0.4\textwidth} - \begin{tabular}{ll} - ...\pemph{interessant+} +e & \gloss{interesting} \\ - ...\pemph{etisch+} +e & \gloss{ethical} \\ - \end{tabular} - \end{minipage} \\ \hline - - 7 & \parbox{0.4\textwidth} - {$\pm$13\% are stems followed by ``+elijk'', often forming adverbs(?). \\ - $\pm$17\% are noun-deriving suffixes ``+heid''/``+heden''.} & - \begin{minipage}{0.4\textwidth} - \begin{tabular}{ll} - ...\pemph{aanvank+} +elijk & \gloss{initially} \\ - ... \pemph{begrijp+} +elijk & \gloss{understandably} \\ - vrij+ \pemph{+heden} ... & \gloss{liberties} \\ - bevoegd+ \pemph{+heid} ... & \gloss{authorisation} \\ - \end{tabular} - \end{minipage} \\ \hline - - 10 & \parbox{0.4\textwidth} - {72\% full words, mostly (compound) nouns or things acting as such. Where $c_{-1}$ is an article, nouns are almost exclusively neuter singular.} & - \begin{minipage}{0.4\textwidth} - \begin{tabular}{ll} - het \pemph{uit+breken} van & \gloss{the outbreak of} \\ - ... \pemph{drie+jaren+plan} ... & \gloss{three-year plan} \\ - \end{tabular} - \end{minipage} \\ \hline - - 16 & \parbox{0.4\textwidth} - {$>$92\% full words, similar to but much larger than Cat. 10. Where $c_{-1}$ is an article, nouns are almost exclusively plural or male/female singular.} & - \begin{minipage}{0.4\textwidth} - \begin{tabular}{ll} - de \pemph{wet+geving} van & \gloss{the legislation of} \\ - deze \pemph{wij+zig+ing} ... & \gloss{this modification} \\ - \end{tabular} - \end{minipage} \\ \hline - \end{tabular} - diff --git a/report/morphology/treelet_bad.pdf b/report/morphology/treelet_bad.pdf deleted file mode 100644 index 67cc710c..00000000 Binary files a/report/morphology/treelet_bad.pdf and /dev/null differ diff --git a/report/morphology/treelet_good.pdf b/report/morphology/treelet_good.pdf deleted file mode 100644 index 3228aa8c..00000000 Binary files a/report/morphology/treelet_good.pdf and /dev/null differ diff --git a/report/morphology/treelet_good_label.pdf b/report/morphology/treelet_good_label.pdf deleted file mode 100644 index cc96c85b..00000000 Binary files a/report/morphology/treelet_good_label.pdf and /dev/null differ diff --git a/report/morphology/treelets.svg b/report/morphology/treelets.svg deleted file mode 100644 index 28d68703..00000000 --- a/report/morphology/treelets.svg +++ /dev/null @@ -1,451 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - image/svg+xml - - - - - - - - - X3 - - - - X - - - en+ +able+ +d - - X - - - - X - - - - - - - - en+ +able+ +d - - X - - - - X3 - - - - - - - - * en+ +able+ +ly address - - X - - - - X - - - - - - - diff --git a/report/np_clustering.tex b/report/np_clustering.tex deleted file mode 100644 index c5992efd..00000000 --- a/report/np_clustering.tex +++ /dev/null @@ -1,317 +0,0 @@ - -\newcommand{\p}{\textbf{p}} - -\chapter{Nonparametric Models} - -In this chapter we describe a Bayesian nonparametric approach to inducing the categories in a synchronous context-free grammar. As discussed in Chapter~\ref{chapter:setup}, we hypothesize that each phrase pair, $\p$, can be clustered on the basis of the contexts it occurs in. Using this as our starting point, we define a generative model where contexts are generated by the (latent) category type of the phrases they occur in. In contrast to most prior work using Bayesian models for synchronous grammar induction \citep{blunsom:nips2008,blunsom:acl2009,zhang:2008}, we do not model parallel sentence pairs directly. Rather, we assume that our corpus is a {\emph collection of contexts}, grouped according to the phrases they occur in, and where each context is conditionally independent of the others, given the type of the category it surrounds. The models used here are thus variations on the Latent Dirichlet Allocation (LDA) model of \cite{blei:2003}. - -In Section~\ref{sec:npmodel} we describe the basic structure of our nonparametric models as well as how inference was carried out. - -\section{Model} -\label{sec:npmodel} - -This section describes the details of the phrase clustering model. Each observed phrase (pair), $\p$, is characterized by a finite mixture of categories, $\theta_{\p}$. The collection of contexts for each phrase, $C_{\p}$, is generated as follows. A category type $z_i$ is drawn from $\theta_{\p}$, and this generates the observed context, $\textbf{c}_i$, according to a category-specific distribution over contexts types, $\phi_{z_i}$. Since we do not know the values of $\theta_{\p}$ and $\phi_z$, we place priors on the distributions, to reflect our prior beliefs about the shape these distributions should have and infer their values from the data we can observe. Specifically, our {\emph a priori} expectation is that both parameters will be relatively peaked, since each phrase, $\p$, should relatively unambiguous belong to particular category, and each category to generate a relatively small number of context strings, $\textbf{c}$. To encode these intuitions, we make use of Pitman-Yor processes \citep{pitman:1997}, which have already been demonstrated to be particularly effective models for language \citep{teh:2006,goldwater:2006}. - -Our model assumes a fixed number of categories, $K$. The category type, $z \in \{ 1 , 2 , \ldots , K \}$, is generated from a PYP with a uniform base distribution: -\begin{align*} -z &| \p & \sim \theta_{\p} \\ -\theta_{\p} &| a_{\p},b_{\p},K & \sim \textrm{PYP}(a_{\p},b_{\p},\frac{1}{K}) -\end{align*} -\noindent As a variation on this, we define a variant of the model with a hierarchical prior on the distribution over categories for a phrase. We share statistics about category use across phrases, encourage a more peaked distribution of categories: -\begin{align*} -z &| \p & \sim \theta_{\p} \\ -\theta_{\p} &| a_{\p},b_{\p} & \sim \textrm{PYP}(a_{\p},b_{\p},\theta_0) \\ -\theta_0 &| a_0,b_0,K & \sim \textrm{PYP}(a_0,b_0,\frac{1}{K}) -\end{align*} - -\noindent Now that we have described how category labels are generated, we describe how contexts are generated from the category. We again model this process using a PYP. Not only does this model tend to favor solutions where contexts used repeatedly are clustered, but it provides a natural way to do smoothing. Since many contexts may be only infrequently observed in the training data, proper smoothing is crucial. Specifically, we can smooth specific contexts by backing off to less specific contexts (e.g., composed of fewer words or word classes). - -The most basic version of our model uses a uniform base distribution over contexts. This model was most useful when generating contexts consisting of a single word or word class (i.e., $\textbf{c}=c_{-1}c_1$) in either the source or target language on either side. - -\begin{align*} -c_{-1}c_1 |& z & \sim \phi_z \\ -\phi_z |& a_z,b_z & \sim \textrm{PYP}(a_z,b_z,\frac{1}{|V|^2}) -\end{align*} - -\noindent When larger contexts were used, the space of these contexts becomes very sparse, so another variant of our model uses a non-uniform base distribution to back off to the probability of generating a smaller context (i.e., $c_{-1}c_1$) as above and then generating the outer context - -\begin{align*} -c_{-2}c_{-1}c_1c_2 |& z & \sim \phi_z \\ -\phi_z |& a_z,b_z & \sim \textrm{PYP}(a_z,b_z,P_1(\cdot|z)) \\ -&P_1(c_{-2}c_{-1}c_1c_2|z)& = \phi^{\textrm{\emph{inner}}}_z(c_{-1}c_1|z) \times \frac{1}{|V|^2} \\ -c_{-1}c_1 |& z & \sim \phi^{\textrm{\emph{inner}}}_z \\ -\phi^{\textrm{\emph{inner}}}_z |& a^{\textrm{\emph{inner}}}_z,b^{\textrm{\emph{inner}}}_z & \sim \textrm{PYP}(a^{\textrm{\emph{inner}}}_z,b^{\textrm{\emph{inner}}}_z,\frac{1}{|V|^2}) -\end{align*} - -\noindent Figure~\ref{fig:np_plate} shows a plate diagram for the two parts of the model that were just described. - -\begin{figure} -\begin{center} -\includegraphics[scale=0.75]{pyp_clustering/np_plate.pdf} -\vspace{-0.3cm} -\end{center} -\caption{Plate diagram for the nonparametric clustering model (hyperparameters omitted). Dashed circles indicate variables that may not be present in every model.} -\label{fig:np_plate} -\end{figure} - -\paragraph{Hyperparameter priors.} The hyperparameters of the PYPs in our models are treated as random variables whose values are inferred from the data and the priors used to characterize the values we expect them to take on. Since we have only a poor prior understanding about what their appropriate values should be, we use vague priors: discount parameters, $a_{(\cdot)}$, are drawn from a uniform Beta distribution ($a_{(\cdot)} \sim \textrm{Beta}(1,1)$) and concentration parameters, $b_{(\cdot)}$, are drawn from a Gamma distribution ($b_{(\cdot)} \sim \textrm{Gamma}(1,1)$). - -\section{Inference} - -Inference in the nonparametric clustering models was performed using Gibbs sampling \citep{geman:1984}, with the continuous parameters ($\theta_{\p}$, $\phi_z$, etc.) integrated out \citep{blunsom:2009}. For the experiments reported below, we sampled for 1,000 iterations. The initial state of the sampler was created by assigning every context in a phrase entirely to a random category. Values for the PYP hyperparameters were resampled after every 10 samples of the Gibbs sampler using the range doubling slice sampling technique \citep{neal:2000,johnson:2009}. Figure~\ref{fig:llh} shows the log-likelihood of the model measured after every 10 samples on an example run of the Urdu-English data with two different numbers of categories. - -The final sample drawn from the model was used to estimate $p(z|\textbf{c},\p)$, and each phrase occurrence was labelled with the $z$ that maximized this probability. - -\begin{figure} -\begin{center} -\includegraphics[scale=0.5]{pyp_clustering/llh.pdf} -\vspace{-0.7cm} -\end{center} -\caption{Log-likelihood versus number of samples with 10 categories (red circles) and 25 categories (blue diamonds) on the Urdu data, 1 target word on either side, hierarchical $\theta_0$, uniform $\phi_0$.} -\label{fig:llh} -\end{figure} - -\section{Experiments} - -This section reports a number of experiments carried out to test the quality of the grammars learned using our nonparametric cluster models. We evaluate them primarily in terms of their performance on translation tasks. Translation quality evaluation is reported using case-insensitive \textsc{bleu} \citep{bleu} with the number of references used depending on the experimental condition (refer to details in the discussion of the corpora used below). - -\subsection{Corpora} - -The experiments reported in this section were carried out primarily on a small Chinese-English corpus from the travel and tourism domain \citep{btec} and a more general-domain Urdu-English corpus, made available by the US National Institute of Standards and Technology (NIST) for the Open MT Evaluation.\footnote{http://www.itl.nist.gov/iad/mig/tests/mt/} Table~\ref{tab:corpbtecur} provides statistics about the training and test data used in the experiments reported in this section. Additionally, this table gives the number of references used to compute the \textsc{bleu} score for a translated document. - -\begin{table}[h] -\caption{Training corpus statistics for BTEC Chinese-English and the NIST Urdu-English data sets.} -\begin{center} -\begin{tabular}{l|r|r} -& BTEC & Urdu \\ -\hline -Sentences & 44,016 & 51,214 \\ -English types & 9,555 & 31,492 \\ -English tokens & 364,297 & 968,013 \\ -Foreign types & 13,664 & 33,757 \\ -Foreign tokens & 333,438 & 1,052,260 \\ -\hline -Dev. sentences & 1,006 & 882 \\ -Test sentences & 506 & 883 \\ -Num. references & 16 & 4 -\end{tabular} -\end{center} -\label{tab:corpbtecur} -\end{table}% - -\subsection{Translation system features} - -In addition to the language model and word penalty, we made use of the following features to score each rule $\textrm{Y} \rightarrow \langle \textbf{f},\textbf{e} \rangle$ used in a derivation. Some features are meaningful only in the context of multi-category grammars. - -\begin{enumerate} -\item The lexical translation log probability of the words in both phrases, $\log \textrm{{\emph lex}}(\textbf{e}|\textbf{f})$, as defined in \cite{Koehn2003}. -\item The inverse lexical translation log probability, $\log \textrm{{\emph lex}}(\textbf{f}|\textbf{e})$. -\item The log frequency of occurrence of the LHS category, $\log f(\textrm{Y})$. This feature always has a value of 0 in the single category (baseline) system. -\item The relative frequency of \textbf{e} given \textbf{f}, collapsing all non-terminals into the symbol X, $f_{\textbf{X}}(\textbf{e}|\textbf{f})$. This is equivalent to the relative frequency of the rule in the 1-category `Hiero' grammar. -\item The inverse relative frequency, $f_{\textbf{X}}(\textbf{f}|\textbf{e})$. -\item The relative frequency of $\langle \textbf{f}, \textbf{e} \rangle$ given Y, $f(\textbf{f}, \textbf{e} | \textrm{Y})$. -\item The log rule count, $\log C(\textrm{Y} \rightarrow \langle \textbf{f},\textbf{e} \rangle)$. -\item A feature with value 1 (creates a count of the number of rules in the derivation). -\end{enumerate} - -\noindent The above feature weights were tuned using the minimum error rate training algorithm (\textsc{mert}), to optimize the 1-best \textsc{bleu} on a held-out development set. - -\subsection{Baseline and supervised benchmark systems} - -We provide a number of baselines to compare our unsupervised syntax systems against. The most important is a single-category system constructed using the procedure described by \cite{chiang:2007} The single-category baseline represents the current state-of-the-art for systems that do not utilize supervised syntax or syntax proxies (like POS tags or syntactic chunks). The random category baselines are provided to give an indication of how a poorly induced syntactic system (for a given $K$) would perform. - -Additionally, we also provide two benchmark systems that use a more sensible set of nonterminal categories. The first uses supervised English (target) language parse trees to annotate the phrases in the grammar as proposed by \cite{samt}. The second (labeled Target POS-only) uses the target language part-of-speech tag for all rules that generate only a single terminal symbol in the target language, and the symbol X otherwise. - -\begin{table} -\caption{Baseline systems} -\begin{center} -\begin{tabular}{r|c|c} -& BTEC & Urdu \\ -\hline -Single category \citep{chiang:2007} & 57.0 & 21.1 \\ -\hline -Random ($K=10$) & 56.0 & 19.8 \\ -Random ($K=25$) & 55.4 & 19.7 \\ -Random ($K=50$) & 55.3 & 19.6 \\ -\hline -Supervised \citep{samt} & 57.8 & 24.5 \\ -Target POS-only ({\emph supervised}) & 56.2 & 22.2 \\ -\end{tabular} -\end{center} -\label{tab:npbaselines} -\end{table}% - -\subsection{Number of categories} - -The number of categories, $K$, is a free parameter in our nonparametric clustering model. In this section, we report results exploring the effect of $K$ on translation quality on the BTEC and Urdu translation tasks. - -Preliminary experiments indicated that single word (to the left and right) target language contexts learned with with a uniform $\phi_0$ and a hierarchical $\theta_0$ produced useful clusters for translation, so we used this as the definition of the context for this experiment. Table~\ref{tab:npvaryk} summarizes the affect of varying $K$ using a single word of target language context, using a uniform $\phi_0$ and a hierarchical $\theta_0$. - -\begin{table}[h] -\caption{Effect of varying $K$, single word left and right target language context, uniform $\phi_0$, hierarchical $\theta_0$.} -\begin{center} -\begin{tabular}{r|c|c} -& BTEC & Urdu \\ -\hline -Single category (baseline) & 57.0 & 21.1 \\ -\hline -$K=10$ & 56.4 & 21.2 \\ -$K=25$ & \textbf{57.5} & \textbf{22.0} \\ -$K=50$ & 56.2 & 21.4 \\ -\end{tabular} -\end{center} -\label{tab:npvaryk} -\end{table}% - - -\subsection{Context types} - -Because the margin of improvement from the 1-category baseline to the supervised condition is much more substantial in the Urdu-English condition than in the BTEC condition, the experiments in this section were carried out only on Urdu. - - -\begin{table}[h] -\caption{Effect of varying the context definition and/or smoothing, $K=25$, hierarchical $\theta_0$; best results in bold. Baseline and benchmark systems also included for reference.} -\begin{center} -\begin{tabular}{r|c|c|c|c} -Context Type & $|\textbf{c}|/2$ & $\phi_0$ & \textsc{bleu} & $H(S|Z)$ \\ -\hline -Baseline ($K=1$) & -- & -- & 20.9 & 4.49 \\ -\hline -Source word & 1 & uniform & 21.7 & 3.25 \\ -Source word class & 1 & uniform & 20.4 & 3.03 \\ -Target word & 1 & uniform & 22.0 & 2.86 \\ -Target word class & 1 & uniform & \textbf{22.3} & \textbf{2.27} \\ -Source word & 2 & 1-word backoff & 21.3 & 3.41 \\ -Source word class & 2 & 1-class backoff & 20.7 & 4.20 \\ -Target word & 2 & 1-word backoff & 20.8 & 3.16 \\ -Target word class & 2 & 1-class backoff & 20.1 & 4.06 \\ -\hline -Supervised \citep{samt} & -- & -- & 24.6 & 0 \\ -Target POS-only ({\emph supervised}) & 1 & uniform & 22.2 & 1.85 \\ -\end{tabular} -\end{center} -\label{tab:npbaselines} -\end{table}% - -\subsection{Correlating the intrinsic metric} - -The experiments discussed in the previous section offer an opportunity to correlate the proposed conditional entropy metric, which measures how well the induced grammar predicts the labels found in the supervised labeling of the corpus. Figure~\ref{fig:intr_correl} shows that there is a reasonable (inverse) correlation between the entropy of the predictive distribution and the \textsc{bleu} score on the test set. - -\begin{figure} -\begin{center} -\includegraphics[scale=0.5]{pyp_clustering/correl.pdf} -\vspace{-0.3cm} -\end{center} -\caption{The intrinsic conditional entropy metric $H(S|Z)$ correlates approximately linearly with \textsc{bleu}.} -\label{fig:intr_correl} -\end{figure} - - -\section{Discussion} - -We now turn to an analysis of the results of the grammars learned using the nonparametric clustering models. - -\subsection{Qualitative analysis of an example grammar} - -Tables~\ref{tab:npexample1} and \ref{tab:npexample2} show a fragment of a 25-category Urdu-English grammar learned using the nonparametric phrase clustering. Rules were selected that maximized the relative frequency $p(\textrm{RHS}|\textrm{LHS})$, filtering out the top 25 (to minimize the appearance of frequent words), and showing only rules consisting of terminal symbols in their right hand side (for clarity). The frequency of each rule type in a grammar filtered for the development set is also given. - -\begin{table}[h] -\caption{Fragment (part 1/2) of 25 category Urdu-English grammar, hierarchical $\theta_0$, uniform $\phi_0$, 1 word context on either side in the target language. Counts indicate the number of distinct rules that rewrite each category type. For clarity, only rules containing only terminal symbols in their RHS are shown.} -\begin{center} -\begin{tabular}{|c|l|c|l|} -\hline -22,386 & $ \textrm{X}^{0} \rightarrow \langle \textrm{EdAlt},\textrm{{\emph court}} \rangle $ &27,604 & $ \textrm{X}^{8} \rightarrow \langle \textrm{tHt},\textrm{{\emph under}} \rangle $ \\ - & $ \textrm{X}^{0} \rightarrow \langle \textrm{bcwN},\textrm{{\emph children}} \rangle $ & & $ \textrm{X}^{8} \rightarrow \langle \textrm{myN},\textrm{{\emph into}} \rangle $ \\ - & $ \textrm{X}^{0} \rightarrow \langle \textrm{lwg},\textrm{{\emph people}} \rangle $ & & $ \textrm{X}^{8} \rightarrow \langle \textrm{yA},\textrm{{\emph or}} \rangle $ \\ - & $ \textrm{X}^{0} \rightarrow \langle \textrm{bcY},\textrm{{\emph children}} \rangle $ & & $ \textrm{X}^{8} \rightarrow \langle \textrm{ky},\textrm{{\emph for}} \rangle $ \\ - & $ \textrm{X}^{0} \rightarrow \langle \textrm{ArkAn},\textrm{{\emph members}} \rangle $ & & $ \textrm{X}^{8} \rightarrow \langle \textrm{kY},\textrm{{\emph for}} \rangle $ \\ -\hline -26,834 & $ \textrm{X}^{1} \rightarrow \langle \textrm{Drwrt},\textrm{{\emph need}} \rangle $ &40,283 & $ \textrm{X}^{9} \rightarrow \langle \textrm{3},\textrm{{\emph 3}} \rangle $ \\ - & $ \textrm{X}^{1} \rightarrow \langle \textrm{SHAfywN},\textrm{{\emph journalists}} \rangle $ & & $ \textrm{X}^{9} \rightarrow \langle \textrm{Hsyn},\textrm{{\emph hussein}} \rangle $ \\ - & $ \textrm{X}^{1} \rightarrow \langle \textrm{bAt},\textrm{{\emph speak}} \rangle $ & & $ \textrm{X}^{9} \rightarrow \langle \textrm{fArwq},\textrm{{\emph farooq}} \rangle $ \\ - & $ \textrm{X}^{1} \rightarrow \langle \textrm{HSh},\textrm{{\emph participate}} \rangle $ & & $ \textrm{X}^{9} \rightarrow \langle \textrm{AqbAl},\textrm{{\emph iqbal}} \rangle $ \\ - & $ \textrm{X}^{1} \rightarrow \langle \textrm{Apyl},\textrm{{\emph appeal}} \rangle $ & & $ \textrm{X}^{9} \rightarrow \langle \textrm{bn},\textrm{{\emph bin}} \rangle $ \\ -\hline -61,592 & $ \textrm{X}^{2} \rightarrow \langle \textrm{kr},\textrm{{\emph the}} \rangle $ &182,196 & $ \textrm{X}^{10} \rightarrow \langle \textrm{yhAN},\textrm{{\emph here}} \rangle $ \\ - & $ \textrm{X}^{2} \rightarrow \langle \textrm{hmArY},\textrm{{\emph our}} \rangle $ & & $ \textrm{X}^{10} \rightarrow \langle \textrm{AjlAs myN},\textrm{{\emph in the meeting}} \rangle $ \\ - & $ \textrm{X}^{2} \rightarrow \langle \textrm{ErAqy},\textrm{{\emph iraqi}} \rangle $ & & $ \textrm{X}^{10} \rightarrow \langle \textrm{AysA},\textrm{{\emph so}} \rangle $ \\ - & $ \textrm{X}^{2} \rightarrow \langle \textrm{dwsrY},\textrm{{\emph other}} \rangle $ & & $ \textrm{X}^{10} \rightarrow \langle \textrm{ElAj},\textrm{{\emph treatment}} \rangle $ \\ - & $ \textrm{X}^{2} \rightarrow \langle \textrm{pr},\textrm{{\emph the}} \rangle $ & & $ \textrm{X}^{10} \rightarrow \langle \textrm{b@hrt},\textrm{{\emph india}} \rangle $ \\ -\hline -98,970 & $ \textrm{X}^{3} \rightarrow \langle \textrm{zndgy},\textrm{{\emph life}} \rangle $ &7,648 & $ \textrm{X}^{11} \rightarrow \langle \textrm{sktA},\textrm{{\emph could}} \rangle $ \\ - & $ \textrm{X}^{3} \rightarrow \langle \textrm{brTAnyh},\textrm{{\emph britain}} \rangle $ & & $ \textrm{X}^{11} \rightarrow \langle \textrm{skyN},\textrm{{\emph can}} \rangle $ \\ - & $ \textrm{X}^{3} \rightarrow \langle \textrm{sEwdy Erb},\textrm{{\emph saudi arabia}} \rangle $ & & $ \textrm{X}^{11} \rightarrow \langle \textrm{tRym},\textrm{{\emph team}} \rangle $ \\ - & $ \textrm{X}^{3} \rightarrow \langle \textrm{AslAm},\textrm{{\emph islam}} \rangle $ & & $ \textrm{X}^{11} \rightarrow \langle \textrm{kAm},\textrm{{\emph work}} \rangle $ \\ - & $ \textrm{X}^{3} \rightarrow \langle \textrm{cyn},\textrm{{\emph china}} \rangle $ & & $ \textrm{X}^{11} \rightarrow \langle \textrm{\$mAly},\textrm{{\emph north}} \rangle $ \\ -\hline -66,916 & $ \textrm{X}^{4} \rightarrow \langle \textrm{AnSAf},\textrm{{\emph justice}} \rangle $ &58,760 & $ \textrm{X}^{12} \rightarrow \langle \textrm{tryn},\textrm{{\emph most}} \rangle $ \\ - & $ \textrm{X}^{4} \rightarrow \langle \textrm{bynk},\textrm{{\emph bank}} \rangle $ & & $ \textrm{X}^{12} \rightarrow \langle \textrm{wAlA},\textrm{{\emph man}} \rangle $ \\ - & $ \textrm{X}^{4} \rightarrow \langle \textrm{nZAm},\textrm{{\emph system}} \rangle $ & & $ \textrm{X}^{12} \rightarrow \langle \textrm{ksy},\textrm{{\emph one}} \rangle $ \\ - & $ \textrm{X}^{4} \rightarrow \langle \textrm{rws},\textrm{{\emph russia}} \rangle $ & & $ \textrm{X}^{12} \rightarrow \langle \textrm{sb},\textrm{{\emph most}} \rangle $ \\ - & $ \textrm{X}^{4} \rightarrow \langle \textrm{srHd},\textrm{{\emph nwfp}} \rangle $ & & $ \textrm{X}^{12} \rightarrow \langle \textrm{bED},\textrm{{\emph some}} \rangle $ \\ -\hline -29,526 & $ \textrm{X}^{5} \rightarrow \langle \textrm{qbwl},\textrm{{\emph accept}} \rangle $ &80,567 & $ \textrm{X}^{13} \rightarrow \langle \textrm{Amrykh kY},\textrm{{\emph the united}} \rangle $ \\ - & $ \textrm{X}^{5} \rightarrow \langle \textrm{cAhtY},\textrm{{\emph want}} \rangle $ & & $ \textrm{X}^{13} \rightarrow \langle \textrm{"},\textrm{{\emph "}} \rangle $ \\ - & $ \textrm{X}^{5} \rightarrow \langle \textrm{jAntY},\textrm{{\emph know}} \rangle $ & & $ \textrm{X}^{13} \rightarrow \langle \textrm{kl},\textrm{{\emph tomorrow}} \rangle $ \\ - & $ \textrm{X}^{5} \rightarrow \langle \textrm{dY},\textrm{{\emph give}} \rangle $ & & $ \textrm{X}^{13} \rightarrow \langle \textrm{mjls},\textrm{{\emph majlis}} \rangle $ \\ - & $ \textrm{X}^{5} \rightarrow \langle \textrm{bcAnY},\textrm{{\emph save}} \rangle $ & & $ \textrm{X}^{13} \rightarrow \langle \textrm{Awr pAkstAn},\textrm{{\emph and pakistan}} \rangle $ \\ -\hline -12,625 & $ \textrm{X}^{6} \rightarrow \langle \textrm{dAxlh},\textrm{{\emph interior}} \rangle $ &111,291 & $ \textrm{X}^{14} \rightarrow \langle \textrm{pAkstAn myN},\textrm{{\emph in pakistan}} \rangle $ \\ - & $ \textrm{X}^{6} \rightarrow \langle \textrm{myjr},\textrm{{\emph major}} \rangle $ & & $ \textrm{X}^{14} \rightarrow \langle \textrm{xw\$},\textrm{{\emph happy}} \rangle $ \\ - & $ \textrm{X}^{6} \rightarrow \langle \textrm{Erb},\textrm{{\emph arab}} \rangle $ & & $ \textrm{X}^{14} \rightarrow \langle \textrm{\$rkt},\textrm{{\emph participated}} \rangle $ \\ - & $ \textrm{X}^{6} \rightarrow \langle \textrm{nY btAyA},\textrm{{\emph told}} \rangle $ & & $ \textrm{X}^{14} \rightarrow \langle \textrm{kAmyAb},\textrm{{\emph succeeded}} \rangle $ \\ - & $ \textrm{X}^{6} \rightarrow \langle \textrm{dAxlh},\textrm{{\emph home}} \rangle $ & & $ \textrm{X}^{14} \rightarrow \langle \textrm{nArAD},\textrm{{\emph angry}} \rangle $ \\ -\hline -53,541 & $ \textrm{X}^{7} \rightarrow \langle \textrm{bcY},\textrm{{\emph child}} \rangle $ &8,547 & $ \textrm{X}^{15} \rightarrow \langle \textrm{hy},\textrm{{\emph is}} \rangle $ \\ - & $ \textrm{X}^{7} \rightarrow \langle \textrm{Hq},\textrm{{\emph right}} \rangle $ & & $ \textrm{X}^{15} \rightarrow \langle \textrm{hw gy},\textrm{{\emph will be}} \rangle $ \\ - & $ \textrm{X}^{7} \rightarrow \langle \textrm{\$hr},\textrm{{\emph city}} \rangle $ & & $ \textrm{X}^{15} \rightarrow \langle \textrm{hw},\textrm{{\emph have}} \rangle $ \\ - & $ \textrm{X}^{7} \rightarrow \langle \textrm{SwrtHAl},\textrm{{\emph situation}} \rangle $ & & $ \textrm{X}^{15} \rightarrow \langle \textrm{rhy hY},\textrm{{\emph is}} \rangle $ \\ - & $ \textrm{X}^{7} \rightarrow \langle \textrm{jng},\textrm{{\emph war}} \rangle $ & & $ \textrm{X}^{15} \rightarrow \langle \textrm{kA},\textrm{{\emph 's}} \rangle $ \\ -\hline -\end{tabular} -\end{center} -\label{tab:npexample1} -\end{table}% - -\begin{table}[h] -\caption{Fragment (part 2/2) of 25 category Urdu-English grammar.} -\begin{center} -\begin{tabular}{|c|l|c|l|} -\hline -40,738 & $ \textrm{X}^{16} \rightarrow \langle \textrm{gyA},\textrm{{\emph .}} \rangle $ &68,633 & $ \textrm{X}^{20} \rightarrow \langle \textrm{m\$yn},\textrm{{\emph machine}} \rangle $ \\ - & $ \textrm{X}^{16} \rightarrow \langle \textrm{lyA},\textrm{{\emph .}} \rangle $ & & $ \textrm{X}^{20} \rightarrow \langle \textrm{myN mwjwd},\textrm{{\emph present in}} \rangle $ \\ - & $ \textrm{X}^{16} \rightarrow \langle \textrm{dy},\textrm{{\emph .}} \rangle $ & & $ \textrm{X}^{20} \rightarrow \langle \textrm{AZhAr},\textrm{{\emph expressing}} \rangle $ \\ - & $ \textrm{X}^{16} \rightarrow \langle \textrm{hy},\textrm{{\emph .}} \rangle $ & & $ \textrm{X}^{20} \rightarrow \langle \textrm{jyt},\textrm{{\emph winning}} \rangle $ \\ - & $ \textrm{X}^{16} \rightarrow \langle \textrm{, pAkstAn},\textrm{{\emph , pakistan}} \rangle $ & & $ \textrm{X}^{20} \rightarrow \langle \textrm{nhyN},\textrm{{\emph not}} \rangle $ \\ -\hline -16,270 & $ \textrm{X}^{17} \rightarrow \langle \textrm{pr},\textrm{{\emph to}} \rangle $ &40,443 & $ \textrm{X}^{21} \rightarrow \langle \textrm{AnkAr},\textrm{{\emph refused}} \rangle $ \\ - & $ \textrm{X}^{17} \rightarrow \langle \textrm{sy},\textrm{{\emph to}} \rangle $ & & $ \textrm{X}^{21} \rightarrow \langle \textrm{khnA},\textrm{{\emph according}} \rangle $ \\ - & $ \textrm{X}^{17} \rightarrow \langle \textrm{AnhwN nY},\textrm{{\emph he further}} \rangle $ & & $ \textrm{X}^{21} \rightarrow \langle \textrm{mlAqAt},\textrm{{\emph met}} \rangle $ \\ - & $ \textrm{X}^{17} \rightarrow \langle \textrm{mstRr jstRs},\textrm{{\emph mr. justice}} \rangle $ & & $ \textrm{X}^{21} \rightarrow \langle \textrm{nY},\textrm{{\emph gave}} \rangle $ \\ - & $ \textrm{X}^{17} \rightarrow \langle \textrm{nY},\textrm{{\emph he}} \rangle $ & & $ \textrm{X}^{21} \rightarrow \langle \textrm{sykwrtRy},\textrm{{\emph security}} \rangle $ \\ -\hline -90,448 & $ \textrm{X}^{18} \rightarrow \langle \textrm{jhAN},\textrm{{\emph where}} \rangle $ &573,610 & $ \textrm{X}^{22} \rightarrow \langle \textrm{w},\textrm{{\emph and}} \rangle $ \\ - & $ \textrm{X}^{18} \rightarrow \langle \textrm{kh},\textrm{{\emph "}} \rangle $ & & $ \textrm{X}^{22} \rightarrow \langle \textrm{)},\textrm{{\emph )}} \rangle $ \\ - & $ \textrm{X}^{18} \rightarrow \langle \textrm{tAkh},\textrm{{\emph so}} \rangle $ & & $ \textrm{X}^{22} \rightarrow \langle \textrm{nY},\textrm{{\emph ,}} \rangle $ \\ - & $ \textrm{X}^{18} \rightarrow \langle \textrm{dryN AvnA'},\textrm{{\emph meanwhile}} \rangle $ & & $ \textrm{X}^{22} \rightarrow \langle \textrm{bEd},\textrm{{\emph after}} \rangle $ \\ - & $ \textrm{X}^{18} \rightarrow \langle \textrm{smyt},\textrm{{\emph including}} \rangle $ & & $ \textrm{X}^{22} \rightarrow \langle \textrm{(},\textrm{{\emph (}} \rangle $ \\ -\hline -64,006 & $ \textrm{X}^{19} \rightarrow \langle \textrm{pwlys},\textrm{{\emph police}} \rangle $ &80,463 & $ \textrm{X}^{23} \rightarrow \langle \textrm{ElAqY},\textrm{{\emph area}} \rangle $ \\ - & $ \textrm{X}^{19} \rightarrow \langle \textrm{whAN},\textrm{{\emph there}} \rangle $ & & $ \textrm{X}^{23} \rightarrow \langle \textrm{bynk},\textrm{{\emph bank}} \rangle $ \\ - & $ \textrm{X}^{19} \rightarrow \langle \textrm{lwg},\textrm{{\emph people}} \rangle $ & & $ \textrm{X}^{23} \rightarrow \langle \textrm{brAdry},\textrm{{\emph community}} \rangle $ \\ - & $ \textrm{X}^{19} \rightarrow \langle \textrm{As},\textrm{{\emph there}} \rangle $ & & $ \textrm{X}^{23} \rightarrow \langle \textrm{Erb},\textrm{{\emph arabia}} \rangle $ \\ - & $ \textrm{X}^{19} \rightarrow \langle \textrm{myrA},\textrm{{\emph i}} \rangle $ & & $ \textrm{X}^{23} \rightarrow \langle \textrm{mslm lyg},\textrm{{\emph muslim league}} \rangle $ \\ -\hline - 22,525 & $ \textrm{X}^{24} \rightarrow \langle \textrm{Drwry},\textrm{{\emph necessary}} \rangle $ &&\\ - & $ \textrm{X}^{24} \rightarrow \langle \textrm{m\$kl},\textrm{{\emph difficult}} \rangle $ &&\\ - & $ \textrm{X}^{24} \rightarrow \langle \textrm{mkml},\textrm{{\emph completed}} \rangle $ && \\ - & $ \textrm{X}^{24} \rightarrow \langle \textrm{jA},\textrm{{\emph being}} \rangle $ &&\\ - & $ \textrm{X}^{24} \rightarrow \langle \textrm{AjAzt},\textrm{{\emph allowed}} \rangle $&& \\ -\hline - -\end{tabular} -\end{center} -\label{tab:npexample2} -\end{table}% - - diff --git a/report/onechap.tex b/report/onechap.tex deleted file mode 100644 index e055028c..00000000 --- a/report/onechap.tex +++ /dev/null @@ -1,54 +0,0 @@ -%!TEX TS-program = pdflatex -%!TEX encoding = UTF-8 Unicode - -\documentclass[11pt]{report} -\usepackage{graphicx} -\usepackage{index} -\usepackage{varioref} -\usepackage{amsmath} -\usepackage{multirow} -\usepackage{theorem} % for examples -\usepackage{alltt} -\usepackage{ulem} -\usepackage{epic,eepic} -\usepackage{boxedminipage} -\usepackage{fancybox} -\usepackage{colortbl} -\usepackage[square]{natbib} -\usepackage{epsfig} -%\usepackage{subfig} -\usepackage{subfigure} -\usepackage{booktabs} -\usepackage{tikz} - -%\usepackage[encapsulated]{CJK} -%\usepackage{ucs} -\usepackage[utf8x]{inputenc} -% use one of bsmi(trad Chinese), gbsn(simp Chinese), min(Japanese), mj(Korean); see: -% /usr/share/texmf-dist/tex/latex/cjk/texinput/UTF8/*.fd -%\newcommand{\cntext}[1]{\begin{CJK}{UTF8}{gbsn}#1\end{CJK}} -\newcommand{\cntext}[1]{} - -\oddsidemargin 0mm -\evensidemargin 5mm -\topmargin -20mm -\textheight 240mm -\textwidth 160mm - - - -\newcommand{\bold}{\it} -\renewcommand{\emph}{\it} - -\makeindex -\theoremstyle{plain} - -\newcommand{\nt}[2]{\textrm{#1}_{\framebox[5pt]{\scriptsize #2}}} -\newcommand{\ind}[1]{{\fboxsep1pt\raisebox{-.5ex}{\fbox{{\tiny #1}}}}} - -\begin{document} - \include{decoding} - \bibliographystyle{apalike} - \bibliography{biblio} - \printindex -\end{document} diff --git a/report/pdf/compare.1stpass.tune.pdf b/report/pdf/compare.1stpass.tune.pdf deleted file mode 100755 index 83f69ffa..00000000 Binary files a/report/pdf/compare.1stpass.tune.pdf and /dev/null differ diff --git a/report/pdf/subset.sh b/report/pdf/subset.sh deleted file mode 100755 index 5e41b3f4..00000000 --- a/report/pdf/subset.sh +++ /dev/null @@ -1,49 +0,0 @@ -ani() { - if [ "$useani" ] ; then - echo "$@" - else - if [ "$2" ] ;then - echo "$2" - else - perl -e '$_=shift;s/.*-//;print' -- "$@" - fi - fi -} - -graph=compare.1stpass.tune.pdf - -pdftk "second session.pdf" cat 209-211 213 output conclusion-subset.pdf - -for useani in '' 1; do - if [ "$useani" ] ; then - aname="-animate" - else - aname= - fi - pdftk "first session.pdf" cat 1 7 8 `ani 10-18` 19-25 26-37 \ - 52-65 66-71 73-76 `ani 77-80` 85-88 \ - `ani 89-101` 102-104 `ani 107-110` 111-118 127-132 \ - 141-144 146-148 \ - 157-159 162 `ani 163-165` 166-168 169 171 `ani 173-178` 179 180-190 192-195 \ - output first-subset$aname.pdf - - pdftk "second session.pdf" cat 70 71 76 79 `ani 82-84` 85 \ - 96 97 98 99 101 \ - output second-subset$aname.pdf - - pdftk C="CLSPclosing.pdf" G=$graph cat 10-11 14 `ani 16-33` 34 `ani 35-44` 45 46 47 48 49 52 `ani 53-58` 59-62 \ - 68 69-74 \ - G \ - 78 \ - 80 `ani 81-82` 85 `ani 87-90` 91-102 \ - output parsing-subset$aname.pdf - - pdftk first-subset$aname.pdf second-subset$aname.pdf parsing-subset$aname.pdf conclusion-subset.pdf \ - cat output subset$aname.pdf - pdftk ws10-graehl.pdf subset$aname.pdf cat output all$aname.pdf - -done - -pdftk 'first session.pdf' cat 1-149 output first.pdf -pdftk 'first.pdf' 'second session.pdf' ../ws10-graehl.pdf cat output all-uncut.pdf - diff --git a/report/pr-clustering/EMPR.pdf b/report/pr-clustering/EMPR.pdf deleted file mode 100644 index fe7b2412..00000000 Binary files a/report/pr-clustering/EMPR.pdf and /dev/null differ diff --git a/report/pr-clustering/EMVSPR.pdf b/report/pr-clustering/EMVSPR.pdf deleted file mode 100644 index c03b41f2..00000000 Binary files a/report/pr-clustering/EMVSPR.pdf and /dev/null differ diff --git a/report/pr-clustering/EMdigram.pdf b/report/pr-clustering/EMdigram.pdf deleted file mode 100644 index aefd14bc..00000000 Binary files a/report/pr-clustering/EMdigram.pdf and /dev/null differ diff --git a/report/pr-clustering/EMreverse.pdf b/report/pr-clustering/EMreverse.pdf deleted file mode 100644 index 095592e7..00000000 Binary files a/report/pr-clustering/EMreverse.pdf and /dev/null differ diff --git a/report/pr-clustering/posterior.tex b/report/pr-clustering/posterior.tex deleted file mode 100644 index 8a199e63..00000000 --- a/report/pr-clustering/posterior.tex +++ /dev/null @@ -1,402 +0,0 @@ -\chapter{Posterior Regularization} -Posterior regularization is an alternative way of clustering the phrases. -Unlike a Bayesian approach where intuitions about the data are -expressed through the priors, -posterior regularization imposes constraints -on posterior distributions of the data. - -In this chapter , we will introduce a basic clustering model with EM -and look at shortcomings of the basic model. This will motivate us for -more complicated posterior regularized models. -\section{Phrase Clustering Model} -As a brief recap, the clustering problem we are working with -is to label phrases with $K$ induced categories, where -$K$ is picked manually. -Phrases are obtained from bi-text data. -We also look at context - words before and after -phrases as cues for clustering. -The relationship between phrases, contexts and categories are -represented with a generative model shown in -Figure \ref{fig:EM}: a phrase picks a -category and then that category generates the contex for the phrase. - -\begin{figure}[h] - \centering - \includegraphics[width=3.0in]{pr-clustering/EMdigram} - \caption{Basic Phrase Clustering Model} - \label{fig:EM} -\end{figure} - -The joint probability of a category $z$ and a context $\textbf{c}$ -given a phrase $\textbf{p}$ is -\begin{equation}\label{eq:NBPost} -P(z,\textbf{c}|\textbf{p})=P(z|\textbf{p})P(\textbf{c}|z). -\end{equation} -$P(z|\textbf{p})$ is distribution of categories given a phrase. -This can be learned from data. -$P(\textbf{c}|z)$ is distribution of context given a category. -Since a context usually contains multiple slots for words, we further -decompose this distribution into independent distributions at -each slot. For example, suppose a context consists of two positions -before and after the phrase. Denote these words as -$c_{-2},c_{-1},c_1,c_2$. -Use $P_{-2},P_{-1},P_1,P_2$ to denote distributions of words at each -position, $P(\textbf{c}|z)$ is decomposed as -\[ -P(\textbf{c}|z)=P_{-2}(c_{-2}|z)P_{-1} -(c_{-1}|z)P_1(c_1|z)P_2(c_2|z). -\] -The posterior probability of a category given a phrase -and a context can be computed by normalizing the joint probability: -\[ -P(z|\textbf{p},\textbf{c})=\frac{P(z,\textbf{c}|\textbf{p})} -{\sum_{i=1,K}P(i,\textbf{c}|\textbf{p})}. -\] -With the mechanisms to compute the posterior probabilities, we can -apply expectation-maximization algorithm (EM) - to learn all the probabilities. -EM algorithm maximizes the data likelihood -\[ -\mathcal{L}= -\sum_{\textbf{p},\textbf{c}} -\log \sum_{z=1}^K P(z,\textbf{c}|\textbf{p}) -\] -EM works by iterating between two steps: -E step computes posterior -distributions according to Equation \ref{eq:NBPost}, -M step updates model parameters with maximum likelihood -estimation as in Equation \ref{eq:MStep}. - -\begin{equation}\label{eq:MStep} -\boldsymbol{\theta}= -\arg\max_{\boldsymbol{\theta}} -\sum_{\textbf{c},\textbf{p}}\sum_z -P(z|\textbf{p},\textbf{c}, -\boldsymbol\theta^{old})\log -P(\textbf{c},\textbf{p}|z,\boldsymbol{\theta}). -\end{equation} - -\section{Sparsity Constraints}\label{sec:pr-sparse} -A common linguistic intuition we have about the phrase -clustering problem is that a phrase should be put into very -few categories, e.g. a verb phrase is unlikely to be used as -a noun phrase. In other words, the categorization of -a phrase should be sparse. -The generative model we proposed above with EM -allows a phrase to be labelled with many tags. As we observed -from the output, EM is using more categories than we wanted for -each phrase. -Posterior regularization -provides a way to enforce sparsity \citep{ganchev:penn:2009}. -The general idea of posterior regularization is to modify -E-step of EM, so that instead of using posterior distribution -as the $q$ distribution directly, the nearest -$q$ -in a constrained space is used - as shown in Figure \ref{fig:EMPR}. - -\begin{figure}[h] - \centering - \includegraphics[width=3.5in]{pr-clustering/EMPR} - \caption{EM with posterior regularization} - \label{fig:EMPR} -\end{figure} - -The constraint we use here is called $L_1/ L_\infty$ -regularization in Ganchev's technical report. The notations -we use here largely follows Ganchev's. -In a more mathematical formulation, for each phrase $\textbf{p}$, -we want the quantity -\begin{equation}\label{eq:sparsity} -\sum_{z=1}^K \max_i P(z|\textbf{p},\textbf{c}_i) -\end{equation} -to be small, where $\textbf{c}_i$ is the context -appeared around the $i$th occurrence of phrase $\textbf{p}$ -throughout the data. This quantity roughly equals -the number of categories phrase $\textbf{p}$ uses. -It is minimized to $1$ if and only if -the posterior distributions $P(z|\textbf{p},\textbf{c}_i)$ -are the same -for all -occurrences of $\textbf{p}$. That is , -$\forall i,j$, -$P(z|\textbf{p},\textbf{c}_i)=P(z|\textbf{p},\textbf{c}_j)$. -For example, Table \ref{tab:sparse} compares two $L_1/L_{\infty}$ -norms of phrases. The first phrase prefers multiple categories -under different contexts, the second phrase prefers -the same category under all contexts. The second phrase -has a much smaller $L_1/L_{\infty}$ norm. - -\begin{table}[h] - \label{tab:sparse} - - \centering - \includegraphics[width=3.5in]{pr-clustering/sparse0} - \caption{$L_1/L_{\infty}$ norm of a phrase - that prefers multiple categories} - \includegraphics[width=3.5in]{pr-clustering/sparse1} - \caption{$L_1/L_{\infty}$ norm of a phrase - that prefers a single phrase} -\end{table} - -Define feature functions for $i$th occurrence of phrase $\textbf{p}$ -with category $j$, -as a function of category $z$: -\[ -\phi_{\textbf{p}ij}(z)= -\begin{cases} -1\text{ if z=j}\\ -0\text{ otherwise} -\end{cases}. -\] -For notation simplicity, for -each phrase category pair, -define variables -$e_{\textbf{p}z}$ to be -$\max_i E_q[\phi_{\textbf{p}iz}]$. Note this is just -a different notation for the term in -Expression \ref{eq:sparsity}. - -The objective we want to optimize becomes: -\[ -\arg\min_{q,c_{\textbf{p}z}} KL(q||P_{\theta}) + -\sigma \sum_{\textbf{p},z}e_{\textbf{p}z} -\] -\[ -\text{ s.t. }\forall \textbf{p},z, -E_q[\phi_{\textbf{p}iz}]\leq e_{\textbf{p}z}, -\] -where $\sigma$ is a constant to control -how strongly the soft constraint should -be enforced. -Using Lagrange Multipliers, this objective can -be optimized in its dual form, -for each phrase $\textbf{p}$: -\[ -\arg\min_{\lambda\geq 0} \log -(\sum_{z,i} P_\theta(z|\textbf{p},\textbf{c}_i) -\exp (-\lambda_{\textbf{p}iz})) -\] -\[ -\text{ s.t. } \forall \textbf{p},z, -\sum_i \lambda_{\textbf{p}iz}\leq \sigma. -\] -This dual objective can be optimized with projected gradient -descent. Notice that each phrase has its own objective and -constraint. The $\lambda$s are not shared acrossed -phrases. Therefore we can optimize the objective -for each phrase separately. It is convenient for parallelizing -the algorithm. It also makes the objective easier to optimize. - -The $q$ distribution we are looking for is then -\[ -q_i(z)\propto P_{\theta}(z|\textbf{p},\textbf{c}_i) -\exp(\lambda_{\textbf{p}iz}). -\] -M-step can be performed as usual by replacing -$P(z|\textbf{p},\textbf{c}, -\boldsymbol\theta^{old})$ with -$q(z)$ in Equation \ref{eq:MStep}. - -\section{Agreement Models}\label{sec:pr-agree} - -Another type of constraint we used is agreement between -different models. The intuition is that if two models run -on the same dataset, it is desirable for them to give the same -output. Suppose two models gives two posterior -distributions of categories -$P_{\theta_1}(z|\textbf{p},\textbf{c})$, -$P_{\theta_2}(z|\textbf{p},\textbf{c})$. The -agreement constraint seeks posterior distributions -$q_1(z),q_2(z)$ -such that $q_1(z)=q_2(z)$ while minimizing -the KL-divergence -$KL(q(z_1)q(z_2)|| -P_{\theta_1}(z|\textbf{p},\textbf{c}) -P_{\theta_1}(z|\textbf{p},\textbf{c}))$. -The solution to $q_1,q_2$ has a simple closed -form derived from Lagrange Multipliers shown in -Equation \ref{eq:AgreePost}. -\begin{equation}\label{eq:AgreePost} -q_1(z)=q_2(z)\propto -\sqrt{P_{\theta_1}(z|\textbf{p},\textbf{c}) -P_{\theta_1}(z|\textbf{p},\textbf{c})} -\end{equation}. - -Since there is no reason to believe in that -phrases generates a category and then generate -a context, it is very natural to come up with a model -that generates in the reverse direction -as shown in Figure \ref{fig:EMreverse}. This model -and the original model should then follow the agreement -constraint. -We also -took advantage of bi-text data and make models -learning from different languages to -agree with each other. - -\begin{figure}[h] - \centering - \includegraphics[width=3.0in]{pr-clustering/EMreverse} - \caption{Generative Model in the reverse Direction} - \label{fig:EMreverse} -\end{figure} - -In the reversed model, -the posterior probability of the labelling of -a context $\textbf{c}$ with -phrase $\textbf{p}$ is -\[ -P(z|\textbf{c},\textbf{p})\propto -P(z|\textbf{c})P(\textbf{p}|z). -\] -Since a phrase contains a variable number of words, -we only look at the first and last word of -a phrase. That is $P(\textbf{p}|z)=P_l(p_l|z)P_r(p_r|z)$, -where $P_l$ and $P_r$ -denotes distributions for words in the first and last position -, $p_l$ and $p_r$ are words in the first and last position. - -The implementation of agreement models again ends up making -a small change to E-step. The $q$ distribution for -a phrase $\textbf{p}$ and a context $\textbf{c}$ -is given by Equation \ref{eq:AgreePost}. -In M-step, both models should update their parameters with $q$ distribution computed as above. -This modified EM is proven to -maximizes the objective: -\[ -\mathcal{L}_1+ -\mathcal{L}_2+ -\sum_{\textbf{p},\textbf{c}} -\log\sum_z\sqrt{P_{\theta_1}(z|\textbf{p},\textbf{c}) -P_{\theta_2}(z|\textbf{p},\textbf{c})}, -\] -where $\mathcal{L}_1$ and $\mathcal{L}_2$ -are log-likelihoods of -each individual model. -\section{Experiments} -As a sanity check, we looked at a few examples produced by -the basic model (EM) -and the posterior regularization (PR) model -with sparsity constraints. Table \ref{tab:EMVSPR} -shows a few examples. - -\begin{table}[h] - \centering - \includegraphics[width=3.5in]{pr-clustering/EMVSPR} - \caption[A few examples comparing EM and PR] - {A few examples comparing EM and PR. - Count of most frequent category shows how - many instances of a phrase are concentrated on - the single most frequent tag. - Number of categories shows how many categories - a phrase is labelled with. By experience as mentioned before, - we want a phrase to use fewer categories. - These numbers are fair indicators of sparsity. - } - \label{tab:EMVSPR} -\end{table} - -The models are formally evaluated with two kinds -of metrics. We feed the clustering output -through the whole translation pipeline -to obtain a BLEU score. We also came up -with an intrinsic evaluation of clustering quality -by comparing against a supervised CFG parser trained on the -tree bank. - -We are mainly working on Urdu-English language pair. -Urdu has very -different word ordering from English. -This leaves us room for improvement over -phrase-based systems. -Here in Table \ref{tab:results} -we show BLEU scores as well as -conditional entropy for each of the models above -on Urdu data. Conditional entropy is computed -as the entropy of ``gold'' labelling given -the predicted clustering. ``Gold'' labelling -distribution -is obtained from Collins parser -trained on Penn Treebank. Since not -all phrases are constituents, we ignored -phrases that don't correspond to any constituents. - -We conducted experiments with various data pre-processing -and tried different models. Number of phrase categories -is fixed at $25$. We chose to only look at -the target side language. The context is set -to be $1$ word to the left and to the right of the phrase. -We chose such a setting because it emperically works better -in the pipeline than other variations. This is also -the case for non-parametric methods. The models as we discussed -in previous sections are EM, EM with sparsity constraint, -agreement of two models in reverse directions and agreement -of two models trained on two languages. We tried our models -with word classes as well. In the context, each word is -replaced with a word class unsupervisedly learned from the data. -The results are shown in Table \ref{tab:results}. - -\begin{table}[h] - \centering - \begin{tabular}{ |*{4}{c|} } - \hline - \multicolumn{2}{|c|}{model} & BLEU & H(Gold$|$Predicted)\\ - \hline - \multicolumn{2}{|c|}{hiero} & 21.1 & 5.77\\ - \multicolumn{2}{|c|}{hiero+POS} & 22.3 & 1.00 \\ - \multicolumn{2}{|c|}{SAMT} & 24.5 & 0.00 \\ - \hline - \multirow{2}{*}{EM} & words & 20.9 & 2.85 \\ - & word classes & 21.54 & 2.86 \\ \hline - \multirow{2}{*}{PR $\sigma=100$}&words & 21.1 & 2.56 \\ - &word classes & 21.7 & 2.36 \\ \hline - \multirow{2}{*}{agree language}&word & 21.7 & 2.80 \\ - &word classes & 21.4 & 2.69\\ \hline - \multirow{2}{*}{agree direction}&word & 21.6 & 2.48\\ - &word classes &22.1 &2.36 \\ \hline - \multirow{2}{*}{non-parametric}&word & 22.0 & 2.86\\ - & word classes&22.3&2.27\\ - \hline - \end{tabular} - \caption - {Evaluation of PR models. - Left column shows BLEU scores - through the translation pipeline. - Right columns shows conditional entropy - of the - } - \label{tab:results} -\end{table} - -In Table \ref{tab:results}, the first three rows -are baseline system. The rest are developed in the workshop. -Hiero is hierachical phrase-based -model with 1 category in all of its SCFG rules. Hiero+POS -is hiero with all words labelled with their POS tags. -SAMT is a syntax based system with a supervised -parser trained on Treebank. EM is the first model mentioned -in the beginning of this chapter. PR $\sigma=100$ is -posterior regularization model with sparsity constraint -explained in Section \ref{sec:pr-sparse}. -$\sigma$ is the constant controls strongness of the constraint. -We picked $\sigma$ by trying different values ranging from -$1$ to $100$. -Agree language and agree direction are models with agreement -constraints mentioned in Section \ref{sec:pr-agree}. Non-parametric -is non-parametric model introduced in the previous chapter. -\section{Conclusion} -The posterior regularization framework has a solid theoretical foundation. -It is shown mathematically to balance between constraint and likelihood. -In our experiments, -we used it to enforce sparsity constraint and agreement constraint and -achieved results comparable to non-parametric method that enforces -sparcity through priors. The algorithm is fairly fast if the constraint -can be decomposed into smaller pieces and compute separately. In our case, -the sparsity constraint for phrases can be decomposed into one small optimization -procedure for each phrase. In practice, our algorithm is much -faster than non-parametric models with Gibbs sampling inference. -The agreement -models are even faster because they are performing almost the same amount -of computation as the simple models trained with EM. diff --git a/report/pr-clustering/pr5long.pdf b/report/pr-clustering/pr5long.pdf deleted file mode 100644 index 7de9dae9..00000000 Binary files a/report/pr-clustering/pr5long.pdf and /dev/null differ diff --git a/report/pr-clustering/sparse0.pdf b/report/pr-clustering/sparse0.pdf deleted file mode 100755 index d103d4db..00000000 Binary files a/report/pr-clustering/sparse0.pdf and /dev/null differ diff --git a/report/pr-clustering/sparse1.pdf b/report/pr-clustering/sparse1.pdf deleted file mode 100755 index 0edad23a..00000000 Binary files a/report/pr-clustering/sparse1.pdf and /dev/null differ diff --git a/report/promise_power.txt b/report/promise_power.txt deleted file mode 100644 index 8c328b7a..00000000 --- a/report/promise_power.txt +++ /dev/null @@ -1,25 +0,0 @@ -cdec option "promise_power" - -po::value()->default_value(0) - -Give more beam budget to more promising previous-pass nodes when pruning - but -allocate the same average beams. 0 means off, 1 means beam proportional to -inside*outside prob, n means nth power (affects just --cubepruning_pop_limit). -note: for the same poplimit, this gives more search error unless very close to 0 -(recommend disabled; even 0.01 is slightly worse than 0) which is a bad sign and -suggests this isn't doing a good job; further it's slightly slower to LM cube -rescore with 0.01 compared to 0, as well as giving (very insignificantly) lower -BLEU. TODO: test under more conditions, or try idea with different formula, or -prob. cube beams. - - -with urdu mt09 2pass 1st pass tuned w/ unigram, prelm_beam_prune=1 scale_prune_srclen - -promise_power: BLEU rescoring time -0: 20.21 1.8s -0.01: 20.16 1.9s -0.1: 20.11 2.0s -(insignificant differences) - -10: 19.7 1.1s -(faster but much worse bleu) diff --git a/report/prune-tuned.pdf b/report/prune-tuned.pdf deleted file mode 100644 index 02666e11..00000000 Binary files a/report/prune-tuned.pdf and /dev/null differ diff --git a/report/prune-untuned.pdf b/report/prune-untuned.pdf deleted file mode 100644 index 03897082..00000000 Binary files a/report/prune-untuned.pdf and /dev/null differ diff --git a/report/prune_results/2pass-hdt b/report/prune_results/2pass-hdt deleted file mode 100644 index d2610931..00000000 --- a/report/prune_results/2pass-hdt +++ /dev/null @@ -1,13 +0,0 @@ -0.03 5.45 -0.05 6.72 -0.08 8.89 -0.12 11.51 -0.17 14.44 -0.25 17.11 -0.3 19.27 -0.4 20.20 -0.6 20.68 -0.8 20.53 -1 20.39 -2 20.51 -3 20.38 diff --git a/report/prune_results/2pass-hdt.pdf b/report/prune_results/2pass-hdt.pdf deleted file mode 100644 index 6f3f43a0..00000000 Binary files a/report/prune_results/2pass-hdt.pdf and /dev/null differ diff --git a/report/prune_results/2pass-hdt.png b/report/prune_results/2pass-hdt.png deleted file mode 100644 index 9c054fbb..00000000 Binary files a/report/prune_results/2pass-hdt.png and /dev/null differ diff --git a/report/prune_results/2pass-hdt0 b/report/prune_results/2pass-hdt0 deleted file mode 100644 index cded1542..00000000 --- a/report/prune_results/2pass-hdt0 +++ /dev/null @@ -1,13 +0,0 @@ -0.03 4.58 -0.05 6.68 -0.08 10.19 -0.12 13.87 -0.17 16.76 -0.25 19.52 -0.3 19.91 -0.4 20.37 -0.6 20.39 -0.8 20.46 -1 20.39 -2 20.41 -3 20.43 diff --git a/report/prune_results/2pass-hdt0.pdf b/report/prune_results/2pass-hdt0.pdf deleted file mode 100644 index a8871a50..00000000 Binary files a/report/prune_results/2pass-hdt0.pdf and /dev/null differ diff --git a/report/prune_results/2pass-hdt0.png b/report/prune_results/2pass-hdt0.png deleted file mode 100644 index d271d0e8..00000000 Binary files a/report/prune_results/2pass-hdt0.png and /dev/null differ diff --git a/report/prune_results/2pass-hdt1 b/report/prune_results/2pass-hdt1 deleted file mode 100644 index 13b7e8c0..00000000 --- a/report/prune_results/2pass-hdt1 +++ /dev/null @@ -1,13 +0,0 @@ -0.03 12.09 -0.05 12.72 -0.08 13.64 -0.12 14.94 -0.17 15.93 -0.25 16.89 -0.3 17.60 -0.4 18.90 -0.6 19.59 -0.8 19.87 -1 20.03 -2 20.33 -3 20.43 diff --git a/report/prune_results/2pass-hdt1.pdf b/report/prune_results/2pass-hdt1.pdf deleted file mode 100644 index 4e2f586c..00000000 Binary files a/report/prune_results/2pass-hdt1.pdf and /dev/null differ diff --git a/report/prune_results/2pass-hdt1.png b/report/prune_results/2pass-hdt1.png deleted file mode 100644 index df7e164f..00000000 Binary files a/report/prune_results/2pass-hdt1.png and /dev/null differ diff --git a/report/prune_results/README b/report/prune_results/README deleted file mode 100644 index d448ce10..00000000 --- a/report/prune_results/README +++ /dev/null @@ -1,21 +0,0 @@ -tuned on urdu baselines (hiero) devtest, test on mt09 - -hdt: single pass (no pruning of -LM forest). these weights were used for the -final +LM rescoring in all cases. (tune BLEU 22.2) - -2pass-hdt: 1st pass weights same as final weights (bad) (tune BLEU ???) - -2pass-hdt0: 1st pass weights tuned without any lm (same final weights as hdt). (tune BLEU 14.7) - -2pass-hdt1: 1st pass weights tuned with unigram lm (same final). (tune BLEU 16.2) - -data files / graphs: 2nd column is BLEU - -2pass-hdt - first column is beam alpha scaled per source word. - -times.2pass-hdt - first column is +LM rescoring time - -space.2pass-hdt - first column is portion of -LM forest edges kept - -It would be nice to graph these with the same scale, or preferably as 3 lines in -the same graph. diff --git a/report/prune_results/cdec-2pass-hdt.ini b/report/prune_results/cdec-2pass-hdt.ini deleted file mode 100644 index c0d034c3..00000000 --- a/report/prune_results/cdec-2pass-hdt.ini +++ /dev/null @@ -1,9 +0,0 @@ -cubepruning_pop_limit=200 -feature_function=LanguageModel /export/ws10smt/data/urdu-english/lm/u2e.en.lm.gz -o 3 -feature_function=WordPenalty -feature_function=ArityPenalty -add_pass_through_rules=true -formalism=scfg -grammar=test.grammar.gz -weights=weights-hdt -prelm_weights=weights-hdt diff --git a/report/prune_results/cdec-2pass-hdt0.ini b/report/prune_results/cdec-2pass-hdt0.ini deleted file mode 100644 index 177cf5b0..00000000 --- a/report/prune_results/cdec-2pass-hdt0.ini +++ /dev/null @@ -1,9 +0,0 @@ -cubepruning_pop_limit=200 -feature_function=LanguageModel /export/ws10smt/data/urdu-english/lm/u2e.en.lm.gz -o 3 -feature_function=WordPenalty -feature_function=ArityPenalty -add_pass_through_rules=true -formalism=scfg -grammar=test.grammar.gz -weights=weights-hdt -prelm_weights=weights-hdt0 diff --git a/report/prune_results/cdec-2pass-hdt1.ini b/report/prune_results/cdec-2pass-hdt1.ini deleted file mode 100644 index da8791c0..00000000 --- a/report/prune_results/cdec-2pass-hdt1.ini +++ /dev/null @@ -1,10 +0,0 @@ -cubepruning_pop_limit=200 -feature_function=LanguageModel lm.gz -o 3 -feature_function=LanguageModel lm.gz -o 1 -n Unigram -feature_function=WordPenalty -feature_function=ArityPenalty -add_pass_through_rules=true -formalism=scfg -grammar=test.grammar.gz -weights=weights-hdt -prelm_weights=weights-hdt1 diff --git a/report/prune_results/cdec-hdt.ini b/report/prune_results/cdec-hdt.ini deleted file mode 100644 index ca00bc7e..00000000 --- a/report/prune_results/cdec-hdt.ini +++ /dev/null @@ -1,8 +0,0 @@ -cubepruning_pop_limit=200 -feature_function=LanguageModel lm.gz -o 3 -feature_function=WordPenalty -feature_function=ArityPenalty -add_pass_through_rules=true -formalism=scfg -grammar=test.grammar.gz -weights=weights-hdt diff --git a/report/prune_results/cdec-hdt1.ini b/report/prune_results/cdec-hdt1.ini deleted file mode 100644 index a58b7ba5..00000000 --- a/report/prune_results/cdec-hdt1.ini +++ /dev/null @@ -1,8 +0,0 @@ -cubepruning_pop_limit=200 -feature_function=LanguageModel lm.gz -o 1 -n Unigram -m 3 -feature_function=WordPenalty -feature_function=ArityPenalty -add_pass_through_rules=true -formalism=scfg -grammar=test.grammar.gz -weights=weights-hdt1 diff --git a/report/prune_results/do.sh b/report/prune_results/do.sh deleted file mode 100755 index b6b22691..00000000 --- a/report/prune_results/do.sh +++ /dev/null @@ -1,8 +0,0 @@ -title="In multipass (TM -> TM+3gram), tuning for 1st pass -> BLEU (y) lost to pruning (x)." \ - n4="tuned_unigram" \ - n2="2ndpass_weights_without_lm" \ - n3="tuned_without_lm" \ - xlbl="post-pruning fraction of edges kept" \ - obase=space.1stpass.tune \ - ymin=0 ymax=21 \ - ./graph.sh space.2pass- hdt hdt0 hdt1 diff --git a/report/prune_results/do.time.sh b/report/prune_results/do.time.sh deleted file mode 100755 index f502881a..00000000 --- a/report/prune_results/do.time.sh +++ /dev/null @@ -1,8 +0,0 @@ -title="In multipass (TM -> TM+3gram), tuning for 1st pass -> BLEU (y) lost to pruning (x)." \ - n4="tuned_unigram" \ - n2="2ndpass_weights_without_lm" \ - n3="tuned_without_lm" \ - xlbl="per-sentence LM rescoring time" \ - obase=time.1stpass.tune \ - ymin=0 ymax=21 \ - ./graph.sh time.2pass- hdt hdt0 hdt1 diff --git a/report/prune_results/graph.sh b/report/prune_results/graph.sh deleted file mode 100755 index 8aa6e228..00000000 --- a/report/prune_results/graph.sh +++ /dev/null @@ -1,66 +0,0 @@ -# see do.sh for usage -d=$(dirname `readlink -f $0`) -. $d/lib.sh - -plboth() { - local o=$1 - local oarg="-landscape" - [ "$portrait" ] && oarg= - shift - set -x - pl -png -o $o.png "$@" -set +x - pl -ps -o $o.ps $oarg "$@" - ps2pdf $o.ps $o.pdf -} - -graph3() { - local y=$1 - local ylbl="$2" - local y2=$3 - local ylbl2="$4" - local y3=$5 - local ylbl3="$6" - local ylbldistance=${7:-'0.7"'} - local name=${name:-$data} - local obase=${obase:-$opre$name.x_`filename_from $xlbl`.$y.`filename_from $ylbl`.$y2.`filename_from $ylbl2`.$y3.`filename_from $ylbl3`} - local of=$obase.png - local ops=$obase.ps - #yrange=0 - local yrange_arg - [ "$ymin" ] && yrange_arg="yrange=$ymin $ymax" - #pointsym=none pointsym2=none - title=${title:-$ylbl $ylbl2 $ylbl3 vs. $xlbl} - xlbl=${xlbl:=x} - showvars_required obase xlbl ylbl ylbl2 ylbl3 - showvars_optional yrange yrange_arg - require_files $data - plboth $obase -prefab lines data=$data x=1 "$yrange_arg" y=$y name="$ylbl" y2=$y2 name2="$ylbl2" y3=$y3 name3="$ylbl3" ylbldistance=$ylbldistance xlbl="$xlbl" title="$title" ystubfmt '%4g' ystubdet="size=6" linedet2="style=1" linedet3="style=3" -scale ${scale:-1.4} - echo $of -} - -pre() { - local pre=$1 - shift - local f - for f in "$@"; do - echo $pre$f - done -} - -main() { - files=( $(pre "$@") ) - data=${data:-compare.$(filename_from $*)} - xlbl=${xlbl:-space} - showvars_required files data xlbl - require_files ${files[*]} - $d/merge-columns.pl ${files[*]} > $data - preview $data - graph3 2 "${n2:-$2}" 3 "${n3:-$3}" 4 "${n4:-$4}" - exit -} - - -if ! [ "$nomain" ] ; then - main "$@";exit -fi diff --git a/report/prune_results/hdt b/report/prune_results/hdt deleted file mode 100644 index 1926d429..00000000 --- a/report/prune_results/hdt +++ /dev/null @@ -1 +0,0 @@ - 20.42 diff --git a/report/prune_results/lib.sh b/report/prune_results/lib.sh deleted file mode 100755 index ff951c64..00000000 --- a/report/prune_results/lib.sh +++ /dev/null @@ -1,89 +0,0 @@ -echo2() { - echo "$@" 1>&2 -} - -errorq() { - echo2 ERROR: "$@" -} - -error() { - errorq "$@" - return 2 -} - -showvars_required() { - echo2 $0 RUNNING WITH REQUIRED VARIABLES: - local k - for k in "$@"; do - eval local v=\$$k - echo2 $k=$v - if [ -z "$v" ] ; then - errorq "required (environment or shell) variable $k not defined!" - return 1 - fi - done - echo2 -} - -showvars_optional() { - echo2 RUNNING WITH OPTIONAL VARIABLES: - local k - for k in "$@"; do - if isset $k ; then - eval local v=\$$k - echo2 $k=$v - else - echo2 UNSET: $k - fi - done - echo2 -} - -require_files() { - 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-uniqin = unique(input); -prediction = zeros(max(input),1); - -p0=1/30114; -for i = 1:length(uniqin) - prediction(uniqin(i)) = b*p0*log((b*p0+uniqin(i))/(b*p0)); -end - -output = prediction(input); - diff --git a/report/pyp_clustering/acl09-short/code/approximations.eps b/report/pyp_clustering/acl09-short/code/approximations.eps deleted file mode 100644 index 67857497..00000000 --- a/report/pyp_clustering/acl09-short/code/approximations.eps +++ /dev/null @@ -1,897 +0,0 @@ -%!PS-Adobe-3.0 EPSF-3.0 -%%Creator: MATLAB, The Mathworks, Inc. 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neg 0 exch rlineto closepath} bdef -/FR {MR stroke} bdef -/PR {MR fill} bdef -/L1i {{currentfile picstr readhexstring pop} image} bdef -/tMatrix matrix def -/MakeOval {newpath tMatrix currentmatrix pop translate scale -0 0 1 0 360 arc tMatrix setmatrix} bdef -/FO {MakeOval stroke} bdef -/PO {MakeOval fill} bdef -/PD {currentlinewidth 2 div 0 360 arc fill - PDlw -1 eq not {PDlw w /PDlw -1 def} if} def -/FA {newpath tMatrix currentmatrix pop translate scale - 0 0 1 5 -2 roll arc tMatrix setmatrix stroke} bdef -/PA {newpath tMatrix currentmatrix pop translate 0 0 moveto scale - 0 0 1 5 -2 roll arc closepath tMatrix setmatrix fill} bdef -/FAn {newpath tMatrix currentmatrix pop translate scale - 0 0 1 5 -2 roll arcn tMatrix setmatrix stroke} bdef -/PAn {newpath tMatrix currentmatrix pop translate 0 0 moveto scale - 0 0 1 5 -2 roll arcn closepath tMatrix setmatrix fill} bdef -/vradius 0 def /hradius 0 def /lry 0 def -/lrx 0 def /uly 0 def /ulx 0 def /rad 0 def -/MRR {/vradius xdef /hradius xdef /lry xdef /lrx xdef /uly xdef - /ulx xdef newpath tMatrix currentmatrix pop ulx hradius add uly - vradius add translate hradius vradius scale 0 0 1 180 270 arc - tMatrix setmatrix lrx hradius sub uly vradius add translate - hradius vradius scale 0 0 1 270 360 arc tMatrix setmatrix - lrx hradius sub lry vradius sub translate hradius vradius scale - 0 0 1 0 90 arc tMatrix setmatrix ulx hradius add lry vradius sub - translate hradius vradius scale 0 0 1 90 180 arc tMatrix setmatrix - closepath} bdef -/FRR {MRR stroke } bdef -/PRR {MRR fill } bdef -/MlrRR {/lry xdef /lrx xdef /uly xdef /ulx xdef /rad lry uly sub 2 div def - newpath tMatrix currentmatrix pop ulx rad add uly rad add translate - rad rad scale 0 0 1 90 270 arc tMatrix setmatrix lrx rad sub lry rad - sub translate rad rad scale 0 0 1 270 90 arc tMatrix setmatrix - closepath} bdef -/FlrRR {MlrRR stroke } bdef -/PlrRR {MlrRR fill } bdef -/MtbRR {/lry xdef /lrx xdef /uly xdef /ulx xdef /rad lrx ulx sub 2 div def - newpath tMatrix currentmatrix pop ulx rad add uly rad add translate - rad rad scale 0 0 1 180 360 arc tMatrix setmatrix lrx rad sub lry rad - sub translate rad rad scale 0 0 1 0 180 arc tMatrix setmatrix - closepath} bdef -/FtbRR {MtbRR stroke } bdef -/PtbRR {MtbRR fill } bdef -/stri 6 array def /dtri 6 array def -/smat 6 array def /dmat 6 array def -/tmat1 6 array def /tmat2 6 array def /dif 3 array def -/asub {/ind2 exch def /ind1 exch def dup dup - ind1 get exch ind2 get sub exch } bdef -/tri_to_matrix { - 2 0 asub 3 1 asub 4 0 asub 5 1 asub - dup 0 get exch 1 get 7 -1 roll astore } bdef -/compute_transform { - dmat dtri tri_to_matrix tmat1 invertmatrix - smat stri tri_to_matrix tmat2 concatmatrix } bdef -/ds {stri astore pop} bdef -/dt {dtri astore pop} bdef -/db {2 copy /cols xdef /rows xdef mul dup 3 mul string - currentfile - 3 index 0 eq {/ASCIIHexDecode filter} - {/ASCII85Decode filter 3 index 2 eq {/RunLengthDecode filter} if } - ifelse exch readstring pop - dup 0 3 index getinterval /rbmap xdef - dup 2 index dup getinterval /gbmap xdef - 1 index dup 2 mul exch getinterval /bbmap xdef pop pop}bdef -/it {gs np dtri aload pop moveto lineto lineto cp c - cols rows 8 compute_transform - rbmap gbmap bbmap true 3 colorimage gr}bdef -/il {newpath moveto lineto stroke}bdef -currentdict end def -%%EndProlog - -%%BeginSetup -MathWorks begin - -0 cap - -end -%%EndSetup - -%%Page: 1 1 -%%BeginPageSetup -%%PageBoundingBox: 89 164 503 676 -MathWorks begin -bpage -%%EndPageSetup - -%%BeginObject: obj1 -bplot - -/dpi2point 12 def -portraitMode 1068 8112 csm - - 0 0 4976 6135 rc -86 dict begin %Colortable dictionary -/c0 { 0.000000 0.000000 0.000000 sr} bdef -/c1 { 1.000000 1.000000 1.000000 sr} bdef -/c2 { 0.900000 0.000000 0.000000 sr} bdef -/c3 { 0.000000 0.820000 0.000000 sr} bdef -/c4 { 0.000000 0.000000 0.800000 sr} bdef -/c5 { 0.910000 0.820000 0.320000 sr} bdef -/c6 { 1.000000 0.260000 0.820000 sr} bdef -/c7 { 0.000000 0.820000 0.820000 sr} bdef -c0 -1 j -1 sg - 0 0 4977 6136 rf -6 w -0 5000 3856 0 0 -5000 647 5460 4 MP -PP --3856 0 0 5000 3856 0 0 -5000 647 5460 5 MP stroke -4 w -DO -SO -6 w -0 sg - 647 5460 mt 4503 5460 L - 647 460 mt 4503 460 L - 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36 36 4070 3771 FO - 36 36 4335 3742 FO -gs 647 460 3857 5001 rc -18 w -0.7 sg -265 -33 266 -34 265 -36 265 -38 265 -42 266 -44 265 -49 265 -52 -266 -60 265 -66 265 -62 265 -96 266 -158 886 3932 14 MP stroke -DA -265 -40 266 -43 265 -46 265 -50 265 -55 266 -60 265 -67 265 -75 -266 -87 265 -100 265 -96 265 -148 266 -242 886 4398 14 MP stroke -SO -6 w -gr - -0.7 sg -0 sg - 850 3932 mt 922 3932 L - 886 3896 mt 886 3968 L -1116 3774 mt 1188 3774 L -1152 3738 mt 1152 3810 L -1381 3678 mt 1453 3678 L -1417 3642 mt 1417 3714 L -1646 3616 mt 1718 3616 L -1682 3580 mt 1682 3652 L -1911 3549 mt 1983 3549 L -1947 3513 mt 1947 3585 L -2177 3490 mt 2249 3490 L -2213 3454 mt 2213 3526 L -2442 3438 mt 2514 3438 L -2478 3402 mt 2478 3474 L -2707 3390 mt 2779 3390 L -2743 3354 mt 2743 3426 L -2973 3344 mt 3045 3344 L -3009 3308 mt 3009 3380 L -3238 3303 mt 3310 3303 L -3274 3267 mt 3274 3339 L -3503 3267 mt 3575 3267 L -3539 3231 mt 3539 3303 L -3768 3228 mt 3840 3228 L -3804 3192 mt 3804 3264 L -4034 3193 mt 4106 3193 L -4070 3157 mt 4070 3229 L -4299 3160 mt 4371 3160 L -4335 3124 mt 4335 3196 L - 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1) -// starting from any odd seed in 0..(2^32 - 1). This version is a recode -// by Shawn Cokus (Cokus@math.washington.edu) on March 8, 1998 of a version by -// Takuji Nishimura (who had suggestions from Topher Cooper and Marc Rieffel in -// July-August 1997). -// -// Effectiveness of the recoding (on Goedel2.math.washington.edu, a DEC Alpha -// running OSF/1) using GCC -O3 as a compiler: before recoding: 51.6 sec. to -// generate 300 million random numbers; after recoding: 24.0 sec. for the same -// (i.e., 46.5% of original time), so speed is now about 12.5 million random -// number generations per second on this machine. -// -// According to the URL -// (and paraphrasing a bit in places), the Mersenne Twister is ``designed -// with consideration of the flaws of various existing generators,'' has -// a period of 2^19937 - 1, gives a sequence that is 623-dimensionally -// equidistributed, and ``has passed many stringent tests, including the -// die-hard test of G. Marsaglia and the load test of P. Hellekalek and -// S. Wegenkittl.'' It is efficient in memory usage (typically using 2506 -// to 5012 bytes of static data, depending on data type sizes, and the code -// is quite short as well). It generates random numbers in batches of 624 -// at a time, so the caching and pipelining of modern systems is exploited. -// It is also divide- and mod-free. -// -// This library is free software; you can redistribute it and/or modify it -// under the terms of the GNU Library General Public License as published by -// the Free Software Foundation (either version 2 of the License or, at your -// option, any later version). This library is distributed in the hope that -// it will be useful, but WITHOUT ANY WARRANTY, without even the implied -// warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See -// the GNU Library General Public License for more details. You should have -// received a copy of the GNU Library General Public License along with this -// library; if not, write to the Free Software Foundation, Inc., 59 Temple -// Place, Suite 330, Boston, MA 02111-1307, USA. -// -// The code as Shawn received it included the following notice: -// -// Copyright (C) 1997 Makoto Matsumoto and Takuji Nishimura. When -// you use this, send an e-mail to with -// an appropriate reference to your work. -// -// It would be nice to CC: when you write. -// - -#include -#include - -// -// uint32 must be an unsigned integer type capable of holding at least 32 -// bits; exactly 32 should be fastest, but 64 is better on an Alpha with -// GCC at -O3 optimization so try your options and see what's best for you -// - -typedef unsigned long uint32; - -#define N (624) // length of state vector -#define M (397) // a period parameter -#define K (0x9908B0DFU) // a magic constant -#define hiBit(u) ((u) & 0x80000000U) // mask all but highest bit of u -#define loBit(u) ((u) & 0x00000001U) // mask all but lowest bit of u -#define loBits(u) ((u) & 0x7FFFFFFFU) // mask the highest bit of u -#define mixBits(u, v) (hiBit(u)|loBits(v)) // move hi bit of u to hi bit of v - -static uint32 state[N+1]; // state vector + 1 extra to not violate ANSI C -static uint32 *next; // next random value is computed from here -static int left = -1; // can *next++ this many times before reloading - - -void seedMT(uint32 seed) - { - // - // We initialize state[0..(N-1)] via the generator - // - // x_new = (69069 * x_old) mod 2^32 - // - // from Line 15 of Table 1, p. 106, Sec. 3.3.4 of Knuth's - // _The Art of Computer Programming_, Volume 2, 3rd ed. - // - // Notes (SJC): I do not know what the initial state requirements - // of the Mersenne Twister are, but it seems this seeding generator - // could be better. It achieves the maximum period for its modulus - // (2^30) iff x_initial is odd (p. 20-21, Sec. 3.2.1.2, Knuth); if - // x_initial can be even, you have sequences like 0, 0, 0, ...; - // 2^31, 2^31, 2^31, ...; 2^30, 2^30, 2^30, ...; 2^29, 2^29 + 2^31, - // 2^29, 2^29 + 2^31, ..., etc. so I force seed to be odd below. - // - // Even if x_initial is odd, if x_initial is 1 mod 4 then - // - // the lowest bit of x is always 1, - // the next-to-lowest bit of x is always 0, - // the 2nd-from-lowest bit of x alternates ... 0 1 0 1 0 1 0 1 ... , - // the 3rd-from-lowest bit of x 4-cycles ... 0 1 1 0 0 1 1 0 ... , - // the 4th-from-lowest bit of x has the 8-cycle ... 0 0 0 1 1 1 1 0 ... , - // ... - // - // and if x_initial is 3 mod 4 then - // - // the lowest bit of x is always 1, - // the next-to-lowest bit of x is always 1, - // the 2nd-from-lowest bit of x alternates ... 0 1 0 1 0 1 0 1 ... , - // the 3rd-from-lowest bit of x 4-cycles ... 0 0 1 1 0 0 1 1 ... , - // the 4th-from-lowest bit of x has the 8-cycle ... 0 0 1 1 1 1 0 0 ... , - // ... - // - // The generator's potency (min. s>=0 with (69069-1)^s = 0 mod 2^32) is - // 16, which seems to be alright by p. 25, Sec. 3.2.1.3 of Knuth. It - // also does well in the dimension 2..5 spectral tests, but it could be - // better in dimension 6 (Line 15, Table 1, p. 106, Sec. 3.3.4, Knuth). - // - // Note that the random number user does not see the values generated - // here directly since reloadMT() will always munge them first, so maybe - // none of all of this matters. In fact, the seed values made here could - // even be extra-special desirable if the Mersenne Twister theory says - // so-- that's why the only change I made is to restrict to odd seeds. - // - - register uint32 x = (seed | 1U) & 0xFFFFFFFFU, *s = state; - register int j; - - for(left=0, *s++=x, j=N; --j; - *s++ = (x*=69069U) & 0xFFFFFFFFU); - } - - -uint32 reloadMT(void) - { - register uint32 *p0=state, *p2=state+2, *pM=state+M, s0, s1; - register int j; - - if(left < -1) - seedMT(4357U); - - left=N-1, next=state+1; - - for(s0=state[0], s1=state[1], j=N-M+1; --j; s0=s1, s1=*p2++) - *p0++ = *pM++ ^ (mixBits(s0, s1) >> 1) ^ (loBit(s1) ? K : 0U); - - for(pM=state, j=M; --j; s0=s1, s1=*p2++) - *p0++ = *pM++ ^ (mixBits(s0, s1) >> 1) ^ (loBit(s1) ? K : 0U); - - s1=state[0], *p0 = *pM ^ (mixBits(s0, s1) >> 1) ^ (loBit(s1) ? K : 0U); - s1 ^= (s1 >> 11); - s1 ^= (s1 << 7) & 0x9D2C5680U; - s1 ^= (s1 << 15) & 0xEFC60000U; - return(s1 ^ (s1 >> 18)); - } - - -inline uint32 randomMT(void) - { - uint32 y; - - if(--left < 0) - return(reloadMT()); - - y = *next++; - y ^= (y >> 11); - y ^= (y << 7) & 0x9D2C5680U; - y ^= (y << 15) & 0xEFC60000U; - y ^= (y >> 18); - return(y); - } - - - - diff --git a/report/pyp_clustering/acl09-short/code/crppred.m b/report/pyp_clustering/acl09-short/code/crppred.m deleted file mode 100644 index 17f22652..00000000 --- a/report/pyp_clustering/acl09-short/code/crppred.m +++ /dev/null @@ -1,12 +0,0 @@ -function output = crppred(input,b) - -uniqin = unique(input); -prediction = zeros(max(input),1); - -p0=1/30114; -for i = 1:length(uniqin) - prediction(uniqin(i)) = b*p0*sum(1./((1:uniqin(i))+b*p0-1)); -end - -output = prediction(input); - diff --git a/report/pyp_clustering/acl09-short/code/crppred_geom.m b/report/pyp_clustering/acl09-short/code/crppred_geom.m deleted file mode 100644 index e6869e4f..00000000 --- a/report/pyp_clustering/acl09-short/code/crppred_geom.m +++ /dev/null @@ -1,12 +0,0 @@ -function output = crppred_geom(input,lengths,b) - - -output = zeros(length(input),1); - -p0=(1/52).^lengths; -a=b*p0; -for i = 1:length(input) - output(i) = a(i)*sum(1./((1:input(i))+a(i)-1)); -end - - diff --git a/report/pyp_clustering/acl09-short/code/logbinmean.m b/report/pyp_clustering/acl09-short/code/logbinmean.m deleted file mode 100644 index 23dbb0ac..00000000 --- a/report/pyp_clustering/acl09-short/code/logbinmean.m +++ /dev/null @@ -1,38 +0,0 @@ -function [ logbinsvalid , meanval, seval ] = logbinmean( frequency, typecount, NBINS , MinCounts ); - -% calculate distribution of frequency -Maxfrequency = max( frequency ); -meanK = mean( frequency ); -linbins = linspace( log10(1) , log10( Maxfrequency ) , NBINS ); -stepb = linbins( 2 ) - linbins( 1 ); - -logbins = 10.^linbins; - -% !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! -LL = length( linbins ) - 1; -for i=1:LL - lowb = linbins( i ); - highb = linbins( i+1 ); - linbinsout( i ) = (highb + lowb) / 2; - - lowb = logbins( i ); - highb = logbins( i+1 ); - step = highb - lowb; - logbinsout( i ) = 10^linbinsout( i ); - - indices = find( frequency >= lowb & frequency < highb); - - meanval(i) = mean(typecount(indices)); - rawcounts(i) = length(indices); - seval(i) = std(typecount(indices))./sqrt(rawcounts(i)); - -end - -valid = 1:LL; -valid( find( rawcounts <= MinCounts )) = []; - -linbinsvalid = linbinsout( valid ); -logbinsvalid = logbinsout( valid ); - -meanval = meanval( valid ); -seval = seval( valid ); diff --git a/report/pyp_clustering/acl09-short/code/noP0pred.m b/report/pyp_clustering/acl09-short/code/noP0pred.m deleted file mode 100644 index f72f1432..00000000 --- a/report/pyp_clustering/acl09-short/code/noP0pred.m +++ /dev/null @@ -1,11 +0,0 @@ -function output = antoniakpred(input,b) - -uniqin = unique(input); -prediction = zeros(max(input),1); - -for i = 1:length(uniqin) - prediction(uniqin(i)) = b*log((b+uniqin(i))/b); -end - -output = prediction(input); - diff --git a/report/pyp_clustering/acl09-short/code/plot0.eps b/report/pyp_clustering/acl09-short/code/plot0.eps deleted file mode 100644 index 6094346a..00000000 --- a/report/pyp_clustering/acl09-short/code/plot0.eps +++ /dev/null @@ -1,633 +0,0 @@ -%!PS-Adobe-3.0 EPSF-3.0 -%%Creator: MATLAB, The Mathworks, Inc. 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-6 w -gr - -6 w - -end %%Color Dict - -eplot -%%EndObject - -epage -end - -showpage - -%%Trailer -%%EOF diff --git a/report/pyp_clustering/acl09-short/code/plot3.pdf b/report/pyp_clustering/acl09-short/code/plot3.pdf deleted file mode 100644 index a3e81faa..00000000 Binary files a/report/pyp_clustering/acl09-short/code/plot3.pdf and /dev/null differ diff --git a/report/pyp_clustering/acl09-short/code/pygibbs3.c b/report/pyp_clustering/acl09-short/code/pygibbs3.c deleted file mode 100644 index 3c2240a1..00000000 --- a/report/pyp_clustering/acl09-short/code/pygibbs3.c +++ /dev/null @@ -1,198 +0,0 @@ -#include -#include - -#define myrand() (double) (((unsigned long) randomMT()) / 4294967296.) - -#define W 30114 -#define N 831190 -#define KWMAX 1000 - -#define NLOOPS 1000 -#define BURNIN 0 -#define SAMPLEFREQ 1 - -#define ALPHA 0.0 // PYB a -//#define GAMMA 1000000000.0 -#define GAMMA .01 // Dirichlet over multinomial P0 - -double BETA; // CRP alpha (PYB b) -int w[N], z[N]; // words, table assignments -int typecount[W], typetot; //# of tables of each type, total # tables -int usedcount[W]; -double ztot[W][KWMAX]; -double k; // total # tables -int nactive; - -void initialise(void); -void anderson(void); -void fileread(void); - -void initialise(void) -{ - int i,j; - - for (i = 1; i < W; i++) { - typecount[i] = 0; - usedcount[i] = 0; - for (j = 0; j < KWMAX; j++) { - ztot[i][j] = 0; - } - } - -} - -void anderson(void) //stochastic Anderson-style initialisation -{ - int i,j, tag; - double max, totprob, r, runtot; - double probs[KWMAX]; - int ind, temp; - - ztot[w[0]][0] = 1; - z[0] = 0; - typecount[w[0]] = 1; - usedcount[w[0]] = 1; - k = 1; - typetot = 1; - - for (i = 1; i < N; i++) { - // printf("%5d\n", w[i]); - max = 0; tag = 0; totprob = 0; - for (j = 0; j < usedcount[w[i]]; j++) { - probs[j] = ztot[w[i]][j] - ALPHA; - totprob += probs[j]; - } - probs[usedcount[w[i]]] = (ALPHA*k+BETA)*((double) typecount[w[i]]+GAMMA)/((double) typetot+W*GAMMA); - totprob += probs[usedcount[w[i]]]; - // printf("%10.6lf\n",totprob); - r = myrand()*totprob; - max = probs[0]; - j = 0; - while (r>max) { - j++; - max += probs[j]; - } - // printf("%5d\n",j); - z[i] = j; - ztot[w[i]][j]++; - if (ztot[w[i]][j]==1) { - typecount[w[i]]++; - usedcount[w[i]]++; - if (usedcount[w[i]]==KWMAX) { - printf("Maximum number of tables exceeded!!!\n"); - } - typetot++; - k++; - } - } -} - -void fileread(void) -{ - int i,j, wt; - FILE *fileptr; - - fileptr = fopen("wsj.dat", "r"); - - for (i = 1; i < N; i++) { - fscanf(fileptr, "%d", &wt); - w[i] = wt-1; - z[i] = 0; - } - printf("Total cases: %10d\n", N); - fclose(fileptr); -} - -main(int argc, char* argv[]) -{ - int i,j,loop,run; - int temp,ind, tag; - double newprob, WBETA; - double probs[KWMAX]; - double max, totprob, r; - int sampcount; - FILE *fileptr; - char filename[30]; - double score; - - if (argc < 2) { - printf("Please provide a value of b\n"); - exit(0); - } - BETA = strtol(argv[1]); - printf("Basic initialising...\n"); - - // you can seed with any uint32, but the best are odds in 0..(2^32 - 1) - seedMT(4157U); - - sprintf(filename,"typecountrecordwsjpeak%0.1f.%0.1f.dat",ALPHA,BETA); - fileptr = fopen(filename, "w"); - - printf("Reading from file...\n"); - fileread(); - - printf("Initialising...\n"); - initialise(); - printf("k = %1.0f, typetot = %d\n",k,typetot); - - printf("Finding start state...\n"); - anderson(); - printf("Beginning burnin...\n"); - for (loop = 0; loop < NLOOPS; loop++) { - for (i = 0; i < N; i++) { - j = z[i]; - ztot[w[i]][j]--; - if (ztot[w[i]][j] == 0) { - if (j==usedcount[w[i]]) { - usedcount[w[i]]--; - } - typecount[w[i]]--; - typetot--; - k--; - } - max = 0; tag = 0; totprob = 0; - for (j = 0; j <= usedcount[w[i]]; j++) { - if (ztot[w[i]][j] > 0) { - probs[j] = ztot[w[i]][j] - ALPHA; - } else { - probs[j] = 0; - if (tag == 0) { - probs[j] = (ALPHA*k+BETA)*(((double) typecount[w[i]])+GAMMA)/(((double) typetot)+((double) W)*GAMMA); - tag = 1; - } - } - totprob += probs[j]; - } - r = myrand()*totprob; - max = probs[0]; - j = 0; - while (r>max) { - j++; - max += probs[j]; - } - z[i] = j; - ztot[w[i]][j]++; - if (ztot[w[i]][j]==1) { - if (j == usedcount[w[i]]) { - usedcount[w[i]]++; - if (usedcount[w[i]]==KWMAX) { - printf("Maximum number of tables exceeded!!!\n"); - } - } - typecount[w[i]]++; - typetot++; - k++; - } - } - printf("Completed sample # %5d\n", loop); - if (k != typetot) printf("k = %1.0f, typetot = %d\n",k,typetot); - if (loop >= BURNIN && loop % SAMPLEFREQ == 0) { - for (i = 0; i < W; i++) { - fprintf(fileptr," %d", typecount[i]); //print (table?) count for each word type - } - fprintf(fileptr,"\n"); - } - } - fclose(fileptr); -} - diff --git a/report/pyp_clustering/acl09-short/code/pygibbs_geom b/report/pyp_clustering/acl09-short/code/pygibbs_geom deleted file mode 100755 index 14ae82f1..00000000 Binary files a/report/pyp_clustering/acl09-short/code/pygibbs_geom and /dev/null differ diff --git a/report/pyp_clustering/acl09-short/code/pygibbs_geom.c b/report/pyp_clustering/acl09-short/code/pygibbs_geom.c deleted file mode 100644 index bafa0416..00000000 --- a/report/pyp_clustering/acl09-short/code/pygibbs_geom.c +++ /dev/null @@ -1,212 +0,0 @@ -#include -#include - -#define myrand() (double) (((unsigned long) randomMT()) / 4294967296.) - -#define W 30114 -#define N 831190 -#define KWMAX 5000 - -#define NLOOPS 11000 -#define BURNIN 1000 -#define SAMPLEFREQ 10 - -#define ALPHA 0.0 // PYB a -//#define GAMMA 1000000000.0 -#define GAMMA .01 // Dirichlet over multinomial P0 - -double BETA; // CRP alpha (PYB b) -int w[N], z[N]; // words, table assignments -double base[N]; // base prob of word under geometric -int typecount[W], typetot; //# of tables of each type, total # tables -int usedcount[W]; -double ztot[W][KWMAX]; -double k; // total # tables -int nactive; - -void initialise(void); -void anderson(void); -void fileread(void); - -void initialise(void) -{ - int i,j; - - for (i = 1; i < W; i++) { - typecount[i] = 0; - usedcount[i] = 0; - for (j = 0; j < KWMAX; j++) { - ztot[i][j] = 0; - } - } - -} - -double base_p(int len) { - double p = 1.0/26; - return pow(p,len)*pow(.5,len); //assume p_# = .5 -} - -void anderson(void) //stochastic Anderson-style initialisation -{ - int i,j, tag; - double max, totprob, r, runtot; - double probs[KWMAX]; - int ind, temp; - - ztot[w[0]][0] = 1; - z[0] = 0; - typecount[w[0]] = 1; - usedcount[w[0]] = 1; - k = 1; - typetot = 1; - - for (i = 1; i < N; i++) { - // printf("%5d\n", w[i]); - max = 0; tag = 0; totprob = 0; - for (j = 0; j < usedcount[w[i]]; j++) { - probs[j] = ztot[w[i]][j] - ALPHA; - totprob += probs[j]; - } - probs[usedcount[w[i]]] = (ALPHA*k+BETA)*base[i]; - totprob += probs[usedcount[w[i]]]; - // printf("%10.6lf\n",totprob); - r = myrand()*totprob; - max = probs[0]; - j = 0; - while (r>max) { - j++; - max += probs[j]; - } - // printf("%5d\n",j); - z[i] = j; - ztot[w[i]][j]++; - if (ztot[w[i]][j]==1) { - typecount[w[i]]++; - usedcount[w[i]]++; - if (usedcount[w[i]]==KWMAX) { - printf("Maximum number of tables exceeded!!!\n"); - } - typetot++; - k++; - } - } -} - -void fileread(void) -{ - int i,j, wt, len; - FILE *fileptr; - - fileptr = fopen("wsj.dat", "r"); - - for (i = 1; i < N; i++) { - fscanf(fileptr, "%d", &wt); - w[i] = wt-1; - z[i] = 0; - } - printf("Total cases: %10d\n", N); - fclose(fileptr); - - fileptr = fopen("wsj_lengths.dat", "r"); - - for (i = 1; i < N; i++) { - fscanf(fileptr, "%d", &len); - base[i] = base_p(len); - } - fclose(fileptr); -} - -main(int argc, char* argv[]) -{ - int i,j,loop,run; - int temp,ind, tag; - double newprob, WBETA; - double probs[KWMAX]; - double max, totprob, r; - int sampcount; - FILE *fileptr; - char filename[30]; - double score; - - if (argc < 2) { - printf("Please provide a value of b\n"); - exit(0); - } - BETA = strtol(argv[1]); - printf("Basic initialising...\n"); - - // you can seed with any uint32, but the best are odds in 0..(2^32 - 1) - seedMT(4157U); - - sprintf(filename,"typecountrecordwsjgeom%0.1f.%0.1f.dat",ALPHA,BETA); - fileptr = fopen(filename, "w"); - - printf("Reading from file...\n"); - fileread(); - - printf("Initialising...\n"); - initialise(); - printf("k = %1.0f, typetot = %d\n",k,typetot); - - printf("Finding start state...\n"); - anderson(); - printf("Beginning burnin...\n"); - for (loop = 0; loop < NLOOPS; loop++) { - for (i = 0; i < N; i++) { - j = z[i]; - ztot[w[i]][j]--; - if (ztot[w[i]][j] == 0) { - if (j==usedcount[w[i]]) { - usedcount[w[i]]--; - } - typecount[w[i]]--; - typetot--; - k--; - } - max = 0; tag = 0; totprob = 0; - for (j = 0; j <= usedcount[w[i]]; j++) { - if (ztot[w[i]][j] > 0) { - probs[j] = ztot[w[i]][j] - ALPHA; - } else { - probs[j] = 0; - if (tag == 0) { - probs[j] = (ALPHA*k+BETA)*base[i]; - tag = 1; - } - } - totprob += probs[j]; - } - r = myrand()*totprob; - max = probs[0]; - j = 0; - while (r>max) { - j++; - max += probs[j]; - } - z[i] = j; - ztot[w[i]][j]++; - if (ztot[w[i]][j]==1) { - if (j == usedcount[w[i]]) { - usedcount[w[i]]++; - if (usedcount[w[i]]==KWMAX) { - printf("Maximum number of tables exceeded!!!\n"); - } - } - typecount[w[i]]++; - typetot++; - k++; - } - } - printf("Completed sample # %5d\n", loop); - if (k != typetot) printf("k = %1.0f, typetot = %d\n",k,typetot); - if (loop >= BURNIN && loop % SAMPLEFREQ == 0) { - for (i = 0; i < W; i++) { - fprintf(fileptr," %d", typecount[i]); //print (table?) count for each word type - } - fprintf(fileptr,"\n"); - } - } - fclose(fileptr); -} - diff --git a/report/pyp_clustering/acl09-short/code/run-peak.prl b/report/pyp_clustering/acl09-short/code/run-peak.prl deleted file mode 100755 index fb1e798a..00000000 --- a/report/pyp_clustering/acl09-short/code/run-peak.prl +++ /dev/null @@ -1,8 +0,0 @@ -#!/usr/bin/perl - -for $i (0..5) { -$beta = 10**$i; -$cmd = "pygibbs_peak $beta\n"; -print $cmd; -`$cmd`; -} diff --git a/report/pyp_clustering/acl09-short/code/run.prl b/report/pyp_clustering/acl09-short/code/run.prl deleted file mode 100755 index ac69559c..00000000 --- a/report/pyp_clustering/acl09-short/code/run.prl +++ /dev/null @@ -1,8 +0,0 @@ -#!/usr/bin/perl - -for $i (0..5) { -$beta = 10**$i; -$cmd = "pygibbs_geom $beta\n"; -print $cmd; -`$cmd`; -} diff --git a/report/pyp_clustering/acl09-short/code/word_lengths.prl b/report/pyp_clustering/acl09-short/code/word_lengths.prl deleted file mode 100755 index 4b4ed03b..00000000 --- a/report/pyp_clustering/acl09-short/code/word_lengths.prl +++ /dev/null @@ -1,21 +0,0 @@ -#!/usr/bin/perl -w -use Getopt::Std; -use File::Basename; -use List::Util qw(max maxstr min minstr reduce shuffle sum); -use lib "$ENV{HOME}/src/perl/"; -use sg_utils; -use strict; -use vars qw(); - -my $usage = "Usage: $0 \n"; - -getopts(''); - -die $usage unless (1); - -while (<>) { -chomp; -print length; -print "\n"; -} - diff --git a/report/pyp_clustering/acl09-short/code/wsjplots2.m b/report/pyp_clustering/acl09-short/code/wsjplots2.m deleted file mode 100644 index eed41846..00000000 --- a/report/pyp_clustering/acl09-short/code/wsjplots2.m +++ /dev/null @@ -1,99 +0,0 @@ - -load wsj - -figure(1) -clf -subplot(1,2,2) -hold on - -for i = 1:9 - a = i/10; - [logbins predicted dummy] = logbinmean(counts,counts.^a,20,20); - ph = plot(log10(logbins),log10(predicted),'k'); - set(ph,'color',[0.7 0.7 0.7],'linewidth',1.5) -end - -for i = 1:9 - a = i/10; - disp(['Loading results for a = ' num2str(a) ]); - - typecountrecord= load([ 'typecountrecordwsjflat' num2str(a) '.1.0.dat']); - - typecountrecordmean = mean(typecountrecord(500:1000,:)); - - save([ 'typecountrecordmeanwsjflat' num2str(a) '.1.0.mat'],'typecountrecordmean'); - - [logbins meanval seval] = logbinmean(counts,typecountrecordmean,20,20) - errorbar(log10(logbins),log10(meanval),log10(meanval+seval)-log10(meanval),log10(meanval-seval)-log10(meanval),'k.'); - drawnow -end - - - - -[logbins meanval seval] = logbinmean(counts,counts,20,20) -[logbins predicted dummy] = logbinmean(counts,counts,20,20) -ph = plot(log10(logbins),log10(predicted),'r'); -hold on -errorbar(log10(logbins),log10(meanval),log10(meanval+seval)-log10(meanval),log10(meanval-seval)-log10(meanval),'k.'); - -set(ph,'color',[0.7 0.7 0.7],'linewidth',1.5) - -set(gca,'xtick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'ytick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'xlim',[-0.1 3.5]) -set(gca,'ylim',[-0.1 3.5]) -set(gca,'xticklabel', {'1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -set(gca,'yticklabel', {'1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); - -title('Pitman-Yor process adaptor') -ylabel('Mean number of lexical entries') -xlabel('Word frequency (n_w)') -box on - -subplot(1,2,1) - -for i = 1:5 - - b = 10^(i-1) - - disp(['Loading results for b = ' num2str(b) ]); - typecountrecord= load([ 'typecountrecordwsjflat0.0.' num2str(b) '.0.dat']); - - typecountrecordmean = mean(typecountrecord(500:1000,:)); - save([ 'typecountrecordmeanwsjflat0.0.' num2str(b) '.0.mat'],'typecountrecordmean'); - - [logbins meanval seval] = logbinmean(counts,typecountrecordmean,20,20) - [logbins predicted dummy] = logbinmean(counts,crppred(counts,b),20,20) -% errorbar(log10(logbins),meanval,seval,'k.'); - hold on - ph = plot(log10(logbins),log10(predicted),'r'); - % ph = plot(log10(logbins),predicted,'r'); - set(ph,'color',[0.7 0.7 0.7],'linewidth',1.5) - errorbar(log10(logbins),log10(meanval),log10(meanval+seval)-log10(meanval),log10(meanval-seval)-log10(meanval),'k.'); -end - -set(gca,'xtick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'ytick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'xlim',[-0.1 3.5]) -set(gca,'ylim',[-0.1 1.5]) -set(gca,'xticklabel', {'1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -set(gca,'yticklabel', {'1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -title('Chinese restaurant process adaptor') -ylabel('Mean number of lexical entries') -xlabel('Word frequency (n_w)') -box on - - diff --git a/report/pyp_clustering/acl09-short/code/wsjplots_acl.m b/report/pyp_clustering/acl09-short/code/wsjplots_acl.m deleted file mode 100644 index 50582e7f..00000000 --- a/report/pyp_clustering/acl09-short/code/wsjplots_acl.m +++ /dev/null @@ -1,74 +0,0 @@ -%wsj_lengths = load([ 'wsj_lengths.dat']); -%save([ 'wsj_lengths.mat'],'wsj_lengths'); -load wsj -load wsj_lengths - -figure(1) -clf - -hold on - -for i = 3:6 - - b = 10^(i-1) - - % plot lines for CRP exact prediction using summation - [logbins predicted dummy] = logbinmean(counts, crppred(counts,b),20,20); - ph = plot(log10(logbins),log10(predicted),'r'); - set(ph,'color',[0.7 0.7 0.7],'linewidth',1.5) - - % plot lines for CRP Antoniak prediction - [logbins predicted dummy] = logbinmean(counts, antoniakpred(counts,b),20,20); - ph = plot(log10(logbins),log10(predicted),'r'); - set(ph,'color',[0.7 0.7 0.7],'linewidth',1.5,'linestyle','--') - - % plot lines for CRP Cohn prediction - %[logbins predicted dummy] = logbinmean(counts, cohnpred(counts,b),20,20); - %ph = plot(log10(logbins),log10(predicted),'r'); - %set(ph,'color',[0.2 0.2 1],'linewidth',1.5,'linestyle','.') - - disp(['Loading results for b = ' num2str(b) ]); - %%% uncomment these lines if .mat file is not yet generated. %%% - %typecountrecord= load([ 'outputs/typecountrecordwsjflat0.0.' num2str(b) '.0.dat']); - %typecountrecordmean = mean(typecountrecord(:,:)); - %save([ 'outputs/typecountrecordmeanwsjflat0.0.' num2str(b) '.0.mat'],'typecountrecordmean'); - load([ 'outputs/typecountrecordmeanwsjflat0.0.' num2str(b) '.0.mat']); - - %plot emprical counts with error bars - [logbins meanval seval] = logbinmean(counts,typecountrecordmean,20,20); - plot(log10(logbins),log10(meanval),'k*'); - %errorbar(log10(logbins),log10(meanval),log10(meanval+seval)-log10(meanval),log10(meanval-seval)-log10(meanval),'k.'); - - disp(['Loading results for b = ' num2str(b) ]); - %%% uncomment these lines if .mat file is not yet generated. %%% - %typecountrecord= load([ 'outputs/typecountrecordwsjpeak0.0.' num2str(b) '.0.dat']); - %typecountrecordmean = mean(typecountrecord(:,:)); - %save([ 'outputs/typecountrecordmeanwsjpeak0.0.' num2str(b) '.0.mat'],'typecountrecordmean'); - load([ 'outputs/typecountrecordmeanwsjpeak0.0.' num2str(b) '.0.mat']); - - %plot emprical counts with error bars - [logbins meanval seval] = logbinmean(counts,typecountrecordmean,20,20); - plot(log10(logbins),log10(meanval),'ko'); - %errorbar(log10(logbins),log10(meanval),log10(meanval+seval)-log10(meanval),log10(meanval-seval)-log10(meanval),'ko'); - -end - -set(gca,'xtick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'ytick',log10([.1:.1:1 2:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'xlim',[-0.1 3.5]) -set(gca,'ylim',[-1.1 2.5]) -set(gca,'FontSize',14) -set(gca,'xticklabel', {'1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -set(gca,'yticklabel', {'0.1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -%title('Chinese restaurant process adaptor') -ylabel('Mean number of lexical entries') -xlabel('Word frequency (n_w)') -legend('Expectation','Antoniak approx.','Empirical, fixed base','Empirical, inferred base','Location','NorthWest') -box on diff --git a/report/pyp_clustering/acl09-short/code/wsjplots_acl_monkeys.m b/report/pyp_clustering/acl09-short/code/wsjplots_acl_monkeys.m deleted file mode 100644 index 33419845..00000000 --- a/report/pyp_clustering/acl09-short/code/wsjplots_acl_monkeys.m +++ /dev/null @@ -1,164 +0,0 @@ -%wsj_lengths = load([ 'wsj_lengths.dat']); -%save([ 'wsj_lengths.mat'],'wsj_lengths'); -load wsj -load wsj_lengths - -figure(1) -clf - -subplot(1,3,1); -hold on - -for i = 2:6 - - b = 10^(i-1) - - disp(['Loading results for b = ' num2str(b) ]); -%%% uncomment these lines if .mat file is not yet generated. %%% - %typecountrecord= load([ 'outputs/typecountrecordwsjflat0.0.' num2str(b) '.0.dat']); - %typecountrecordmean = mean(typecountrecord(500:999,:)); - %save([ 'outputs/typecountrecordmeanwsjflat0.0.' num2str(b) '.0.mat'],'typecountrecordmean'); - load([ 'outputs/typecountrecordmeanwsjflat0.0.' num2str(b) '.0.mat']); - - % plot lines for CRP exact prediction using summation - [logbins predicted dummy] = logbinmean(counts, crppred(counts,b),20,20); - ph = plot(log10(logbins),log10(predicted),'r'); - set(ph,'color',[0.7 0.7 0.7],'linewidth',1.5) - - % plot lines for CRP Antoniak prediction - [logbins predicted dummy] = logbinmean(counts, antoniakpred(counts,b),20,20); - ph = plot(log10(logbins),log10(predicted),'r'); - set(ph,'color',[0.7 0.7 0.7],'linewidth',1.5,'linestyle','--') - - % plot lines for incorrect CRP Antoniak prediction (ACL07) - %[logbins predicted dummy] = logbinmean(counts, noP0pred(counts,b),20,20); - %ph = plot(log10(logbins),log10(predicted),'r'); - %set(ph,'color',[0.7 0.7 0.7],'linewidth',1.5,'linestyle','-.') - - % plot lines for CRP Cohn prediction - %[logbins predicted dummy] = logbinmean(counts, cohnpred(counts,b),20,20); - %ph = plot(log10(logbins),log10(predicted),'r'); - %set(ph,'color',[0.2 0.2 1],'linewidth',1.5,'linestyle','.') - - %plot emprical counts with error bars - [logbins meanval seval] = logbinmean(counts,typecountrecordmean,20,20); - errorbar(log10(logbins),log10(meanval),log10(meanval+seval)-log10(meanval),log10(meanval-seval)-log10(meanval),'k.'); -end - -set(gca,'xtick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'ytick',log10([.1:.1:1 2:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'xlim',[-0.1 3.5]) -set(gca,'ylim',[-1.1 1.5]) -set(gca,'FontSize',14) -set(gca,'xticklabel', {'1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -set(gca,'yticklabel', {'0.1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -%title('Chinese restaurant process adaptor') -ylabel('Mean number of lexical entries') -xlabel('Word frequency (n_w)') -legend('Expectation','Antoniak approx.','Empirical','Location','NorthWest') -box on - - -subplot(1,3,2); -hold on - -for i =2:6 - - b = 10^(i-1) - - disp(['Loading results for b = ' num2str(b) ]); -%%% uncomment these lines if .mat file is not yet generated. %%% - %typecountrecord= load([ 'outputs/typecountrecordwsjpeak0.0.' num2str(b) '.0.dat']); - %typecountrecordmean = mean(typecountrecord(500:999,:)); - %save([ 'outputs/typecountrecordmeanwsjpeak0.0.' num2str(b) '.0.mat'],'typecountrecordmean'); - load([ 'outputs/typecountrecordmeanwsjpeak0.0.' num2str(b) '.0.mat']); - - % plot lines for CRP exact prediction using summation - [logbins predicted dummy] = logbinmean(counts, crppred(counts,b),20,20); - ph = plot(log10(logbins),log10(predicted),'r'); - set(ph,'color',[0.7 0.7 0.7],'linewidth',1.5) - - %plot emprical counts with error bars - [logbins meanval seval] = logbinmean(counts,typecountrecordmean,20,20); - errorbar(log10(logbins),log10(meanval),log10(meanval+seval)-log10(meanval),log10(meanval-seval)-log10(meanval),'k.'); -end - -set(gca,'xtick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'ytick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'xlim',[-0.1 3.5]) -set(gca,'ylim',[-.1 2.5]) -set(gca,'FontSize',14) -set(gca,'xticklabel', {'1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -set(gca,'yticklabel', {...%'0.1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -%title('Chinese restaurant process adaptor') -ylabel('Mean number of lexical entries') -xlabel('Word frequency (n_w)') -legend('Expectation','Location','NorthWest') -box on -%axis square - - -subplot(1,3,3); -hold on - -for i =2:6 - - b = 10^(i-1) - - disp(['Loading results for b = ' num2str(b) ]); -%%% uncomment these lines if .mat file is not yet generated. %%% - %typecountrecord= load([ 'outputs/typecountrecordwsjgeom0.0.' num2str(b) '.0.dat']); - %typecountrecordmean = mean(typecountrecord(500:999,:)); - %save([ 'outputs/typecountrecordmeanwsjgeom0.0.' num2str(b) '.0.mat'],'typecountrecordmean'); - load([ 'outputs/typecountrecordmeanwsjgeom0.0.' num2str(b) '.0.mat']); - - % plot lines for CRP exact prediction using summation -% [logbins meaneval seval] = logbinmean(counts, crppred_geom(counts,wsj_lengths,b),20,20) -[logbins meaneval seval] = logbinmean(counts, crppred(counts,b),20,20) - plot(log10(logbins),log10(meaneval),'r.'); -%errorbar(log10(logbins),log10(meanval),log10(meanval+seval)-log10(meanval),log10(meanval-seval)-log10(meanval),'r.'); -% ph = plot(log10(logbins),log10(meaneval),'r'); -% set(ph,'color',[0.7 0.7 0.7],'linewidth',1.5) - - %plot emprical counts with error bars - [logbins meanval seval] = logbinmean(counts,typecountrecordmean,20,20); - errorbar(log10(logbins),log10(meanval),log10(meanval+seval)-log10(meanval),log10(meanval-seval)-log10(meanval),'k.'); -end - -set(gca,'xtick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'ytick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'xlim',[-0.1 3.5]) -set(gca,'ylim',[-.1 2.5]) -set(gca,'FontSize',14) -set(gca,'xticklabel', {'1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -set(gca,'yticklabel', {...%'0.1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -%title('Chinese restaurant process adaptor') -ylabel('Mean number of lexical entries') -xlabel('Word frequency (n_w)') -legend('Expectation','Location','NorthWest') -box on -hold off -%axis square - - diff --git a/report/pyp_clustering/acl09-short/code/wsjplots_acl_pair.m b/report/pyp_clustering/acl09-short/code/wsjplots_acl_pair.m deleted file mode 100644 index 1d07e54c..00000000 --- a/report/pyp_clustering/acl09-short/code/wsjplots_acl_pair.m +++ /dev/null @@ -1,117 +0,0 @@ -%wsj_lengths = load([ 'wsj_lengths.dat']); -%save([ 'wsj_lengths.mat'],'wsj_lengths'); -load wsj -load wsj_lengths - -figure(1) -clf - -subplot(1,2,1); -hold on - -for i = 3:6 - - b = 10^(i-1) - - disp(['Loading results for b = ' num2str(b) ]); -%%% uncomment these lines if .mat file is not yet generated. %%% - %typecountrecord= load([ 'outputs/typecountrecordwsjflat0.0.' num2str(b) '.0.dat']); - %typecountrecordmean = mean(typecountrecord(:,:)); - %save([ 'outputs/typecountrecordmeanwsjflat0.0.' num2str(b) '.0.mat'],'typecountrecordmean'); - load([ 'outputs/typecountrecordmeanwsjflat0.0.' num2str(b) '.0.mat']); - - % plot lines for CRP exact prediction using summation - [logbins predicted dummy] = logbinmean(counts, crppred(counts,b),20,20); - ph = plot(log10(logbins),log10(predicted),'r'); - set(ph,'color',[0.7 0.7 0.7],'linewidth',1.5) - - % plot lines for CRP Antoniak prediction - [logbins predicted dummy] = logbinmean(counts, antoniakpred(counts,b),20,20); - ph = plot(log10(logbins),log10(predicted),'r'); - set(ph,'color',[0.7 0.7 0.7],'linewidth',1.5,'linestyle','--') - - %plot lines for incorrect CRP Antoniak prediction (ACL07) - %[logbins predicted dummy] = logbinmean(counts, noP0pred(counts,b),20,20); - %ph = plot(log10(logbins),log10(predicted),'r'); - %set(ph,'color',[0.7 0.7 0.7],'linewidth',1.5,'linestyle',':') - - % plot lines for CRP Cohn prediction - %[logbins predicted dummy] = logbinmean(counts, cohnpred(counts,b),20,20); - %ph = plot(log10(logbins),log10(predicted),'r'); - %set(ph,'color',[0.2 0.2 1],'linewidth',1.5,'linestyle','.') - - %plot emprical counts with error bars - [logbins meanval seval] = logbinmean(counts,typecountrecordmean,20,20); - errorbar(log10(logbins),log10(meanval),log10(meanval+seval)-log10(meanval),log10(meanval-seval)-log10(meanval),'k.'); -end - -set(gca,'xtick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'ytick',log10([.1:.1:1 2:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'xlim',[-0.1 3.5]) -set(gca,'ylim',[-1.1 1.5]) -set(gca,'FontSize',14) -set(gca,'xticklabel', {'1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -set(gca,'yticklabel', {'0.1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -%title('Chinese restaurant process adaptor') -ylabel('Mean number of lexical entries') -xlabel('Word frequency (n_w)') -legend('Expectation','Antoniak approx.','Empirical','Location','NorthWest') -box on - - -subplot(1,2,2); -hold on - -for i =3:6 - - b = 10^(i-1) - - disp(['Loading results for b = ' num2str(b) ]); -%%% uncomment these lines if .mat file is not yet generated. %%% - %typecountrecord= load([ 'outputs/typecountrecordwsjpeak0.0.' num2str(b) '.0.dat']); - %typecountrecordmean = mean(typecountrecord(:,:)); - %save([ 'outputs/typecountrecordmeanwsjpeak0.0.' num2str(b) '.0.mat'],'typecountrecordmean'); - load([ 'outputs/typecountrecordmeanwsjpeak0.0.' num2str(b) '.0.mat']); - - % plot lines for CRP exact prediction using summation - [logbins predicted dummy] = logbinmean(counts, crppred(counts,b),20,20); - ph = plot(log10(logbins),log10(predicted),'r'); - set(ph,'color',[0.7 0.7 0.7],'linewidth',1.5) - - %plot lines for incorrect CRP Antoniak prediction (ACL07) - [logbins predicted dummy] = logbinmean(counts, noP0pred(counts,b),20,20); - ph = plot(log10(logbins),log10(predicted),'r'); - set(ph,'color',[0.7 0.7 0.7],'linewidth',1.5,'linestyle','-.') - - %plot emprical counts with error bars - [logbins meanval seval] = logbinmean(counts,typecountrecordmean,20,20); - errorbar(log10(logbins),log10(meanval),log10(meanval+seval)-log10(meanval),log10(meanval-seval)-log10(meanval),'k.'); -end - -set(gca,'xtick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'ytick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'xlim',[-0.1 3.5]) -set(gca,'ylim',[-.1 2.5]) -set(gca,'FontSize',14) -set(gca,'xticklabel', {'1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -set(gca,'yticklabel', {...%'0.1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -%title('Chinese restaurant process adaptor') -ylabel('Mean number of lexical entries') -xlabel('Word frequency (n_w)') -legend('Expectation','GGJ07 approx.','Empirical','Location','NorthWest') -box on -%axis square \ No newline at end of file diff --git a/report/pyp_clustering/acl09-short/code/wsjplots_acl_talk0.m b/report/pyp_clustering/acl09-short/code/wsjplots_acl_talk0.m deleted file mode 100644 index dc54dea4..00000000 --- a/report/pyp_clustering/acl09-short/code/wsjplots_acl_talk0.m +++ /dev/null @@ -1,54 +0,0 @@ -%wsj_lengths = load([ 'wsj_lengths.dat']); -%save([ 'wsj_lengths.mat'],'wsj_lengths'); -load wsj -load wsj_lengths - -figure(1) -clf - -hold on - -%colors = [0 0 0; 0 0 1; 1 0 0; 0 1 0]; %pure black, red, blue, green -colors = [0 0 0; 1 .4 .2; .4 .4 1; 0 .7 .5]; %same but less garish -%colors = [0 0 0; .6 .4 .4; .9 .6 .6; 1 .8 .8]; %shades of pink -%colors = [0 0 0; .3 .3 1; .4 .8 1; .5 1 .8]; %blue/green - -for i = 9-[3:6] - - b = 10^(i-1) - - disp(['Loading results for b = ' num2str(b) ]); - %%% uncomment these lines if .mat file is not yet generated. %%% - %typecountrecord= load([ 'outputs/typecountrecordwsjflat0.0.' num2str(b) '.0.dat']); - %typecountrecordmean = mean(typecountrecord(:,:)); - %save([ 'outputs/typecountrecordmeanwsjflat0.0.' num2str(b) '.0.mat'],'typecountrecordmean'); - load([ 'outputs/typecountrecordmeanwsjflat0.0.' num2str(b) '.0.mat']); - - %plot emprical counts with error bars - [logbins meanval seval] = logbinmean(counts,typecountrecordmean,20,20); - ph = plot(log10(logbins),log10(meanval)); - set(ph,'color',colors(i-2,:),'linestyle','o','linewidth',2,'markersize',10); - %errorbar(log10(logbins),log10(meanval),log10(meanval+seval)-log10(meanval),log10(meanval-seval)-log10(meanval),'k.'); - -end - -set(gca,'xtick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'ytick',log10([.1:.1:1 2:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'xlim',[-0.1 3.5]) -set(gca,'ylim',[-.1 2]) -set(gca,'FontSize',16) -set(gca,'xticklabel', {'1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -set(gca,'yticklabel', {'0.1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -%title('Chinese restaurant process adaptor') -ylabel('Mean number of lexical entries (tables)') -xlabel('Word frequency (n_w)') -labs = {'\alpha = 100000','\alpha = 10000','\alpha = 1000','\alpha = 100'}; -legend(labs,'Location','NorthWest') -box on diff --git a/report/pyp_clustering/acl09-short/code/wsjplots_acl_talk1.m b/report/pyp_clustering/acl09-short/code/wsjplots_acl_talk1.m deleted file mode 100644 index dd3615ac..00000000 --- a/report/pyp_clustering/acl09-short/code/wsjplots_acl_talk1.m +++ /dev/null @@ -1,59 +0,0 @@ -%wsj_lengths = load([ 'wsj_lengths.dat']); -%save([ 'wsj_lengths.mat'],'wsj_lengths'); -load wsj -load wsj_lengths - -figure(1) -clf - -hold on - -%colors = [0 0 0; 0 0 1; 1 0 0; 0 1 0]; %pure black, red, blue, green -colors = [0 0 0; 1 .4 .2; .4 .4 1; 0 .7 .5]; %same but less garish -%colors = [0 0 0; .6 .4 .4; .9 .6 .6; 1 .8 .8]; %shades of pink -%colors = [0 0 0; .3 .3 1; .4 .8 1; .5 1 .8]; %blue/green - -for i = 3:6 - - b = 10^(i-1) - - disp(['Loading results for b = ' num2str(b) ]); - %%% uncomment these lines if .mat file is not yet generated. %%% - %typecountrecord= load([ 'outputs/typecountrecordwsjflat0.0.' num2str(b) '.0.dat']); - %typecountrecordmean = mean(typecountrecord(:,:)); - %save([ 'outputs/typecountrecordmeanwsjflat0.0.' num2str(b) '.0.mat'],'typecountrecordmean'); - load([ 'outputs/typecountrecordmeanwsjflat0.0.' num2str(b) '.0.mat']); - - %plot emprical counts with error bars - [logbins meanval seval] = logbinmean(counts,typecountrecordmean,20,20); - ph = plot(log10(logbins),log10(meanval)); - set(ph,'color',colors(i-2,:),'linestyle','o','linewidth',2,'markersize',8); - %errorbar(log10(logbins),log10(meanval),log10(meanval+seval)-log10(meanval),log10(meanval-seval)-log10(meanval),'k.'); - - % plot lines for CRP exact prediction using summation - [logbins predicted dummy] = logbinmean(counts, crppred(counts,b),20,20); - ph = plot(log10(logbins),log10(predicted),'r'); - set(ph,'color',colors(i-2,:),'linewidth',2); - -end - -set(gca,'xtick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'ytick',log10([.1:.1:1 2:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'xlim',[-0.1 3.5]) -set(gca,'ylim',[-.1 2]) -set(gca,'FontSize',16) -set(gca,'xticklabel', {'1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -set(gca,'yticklabel', {'0.1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -%title('Chinese restaurant process adaptor') -ylabel('Mean number of lexical entries (tables)') -xlabel('Word frequency (n_w)') -labs = {'Empirical','Expectation'}; -legend(labs,'Location','NorthWest') -box on diff --git a/report/pyp_clustering/acl09-short/code/wsjplots_acl_talk2.m b/report/pyp_clustering/acl09-short/code/wsjplots_acl_talk2.m deleted file mode 100644 index dd039289..00000000 --- a/report/pyp_clustering/acl09-short/code/wsjplots_acl_talk2.m +++ /dev/null @@ -1,58 +0,0 @@ -%wsj_lengths = load([ 'wsj_lengths.dat']); -%save([ 'wsj_lengths.mat'],'wsj_lengths'); -load wsj -load wsj_lengths - -figure(1) -clf - -hold on - -%colors = [0 0 0; 0 0 1; 1 0 0; 0 1 0]; %pure black, red, blue, green -colors = [0 0 0; 1 .4 .2; .4 .4 1; 0 .7 .5]; %same but less garish -%colors = [0 0 0; .6 .4 .4; .9 .6 .6; 1 .8 .8]; %shades of pink -%colors = [0 0 0; .3 .3 1; .4 .8 1; .5 1 .8]; %blue/green - -for i = 3:6 - - b = 10^(i-1) - - disp(['Loading results for b = ' num2str(b) ]); - %%% uncomment these lines if .mat file is not yet generated. %%% - %typecountrecord= load([ 'outputs/typecountrecordwsjflat0.0.' num2str(b) '.0.dat']); - %typecountrecordmean = mean(typecountrecord(:,:)); - %save([ 'outputs/typecountrecordmeanwsjflat0.0.' num2str(b) '.0.mat'],'typecountrecordmean'); - load([ 'outputs/typecountrecordmeanwsjflat0.0.' num2str(b) '.0.mat']); - - % plot lines for CRP exact prediction using summation - [logbins predicted dummy] = logbinmean(counts, crppred(counts,b),20,20); - ph = plot(log10(logbins),log10(predicted),'r'); - set(ph,'color',colors(i-2,:),'linewidth',2); - - % plot lines for CRP Antoniak prediction - [logbins predicted dummy] = logbinmean(counts, antoniakpred(counts,b),20,20); - ph = plot(log10(logbins),log10(predicted),'r'); - set(ph,'color',colors(i-2,:),'linewidth',2,'linestyle','--') - -end - -set(gca,'xtick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'ytick',log10([.1:.1:1 2:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'xlim',[-0.1 3.5]) -set(gca,'ylim',[-1.1 2]) -set(gca,'FontSize',16) -set(gca,'xticklabel', {'1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -set(gca,'yticklabel', {'0.1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -%title('Chinese restaurant process adaptor') -ylabel('Mean number of lexical entries (tables)') -xlabel('Word frequency (n_w)') -labs = {'Expectation','Antoniak approximation'}; -legend(labs,'Location','NorthWest') -box on diff --git a/report/pyp_clustering/acl09-short/code/wsjplots_acl_talk3.m b/report/pyp_clustering/acl09-short/code/wsjplots_acl_talk3.m deleted file mode 100644 index 8d570b7a..00000000 --- a/report/pyp_clustering/acl09-short/code/wsjplots_acl_talk3.m +++ /dev/null @@ -1,74 +0,0 @@ -%wsj_lengths = load([ 'wsj_lengths.dat']); -%save([ 'wsj_lengths.mat'],'wsj_lengths'); -load wsj -load wsj_lengths - -figure(1) -clf - -hold on - -%colors = [0 0 0; 0 0 1; 1 0 0; 0 1 0]; %pure black, red, blue, green -colors = [0 0 0; 1 .4 .2; .4 .4 1; 0 .7 .5]; %similar but less garish -%colors = [0 0 0; .6 .4 .4; .9 .6 .6; 1 .8 .8]; %shades of pink -%colors = [0 0 0; .3 .3 1; .4 .8 1; .5 1 .8]; %blue/green - -for i = 3:6 - col = colors(i-2,:); - b = 10^(i-1) - - % plot lines for CRP exact prediction using summation - [logbins predicted dummy] = logbinmean(counts, crppred(counts,b),20,20); - ph = plot(log10(logbins),log10(predicted)); - set(ph,'color',col,'linewidth',2); - - disp(['Loading results for b = ' num2str(b) ]); - %%% uncomment these lines if .mat file is not yet generated. %%% - %typecountrecord= load([ 'outputs/typecountrecordwsjflat0.0.' num2str(b) '.0.dat']); - %typecountrecordmean = mean(typecountrecord(:,:)); - %save([ 'outputs/typecountrecordmeanwsjflat0.0.' num2str(b) '.0.mat'],'typecountrecordmean'); - load([ 'outputs/typecountrecordmeanwsjflat0.0.' num2str(b) '.0.mat']); - - %plot emprical counts with error bars - [logbins meanval seval] = logbinmean(counts,typecountrecordmean,20,20); - ph = plot(log10(logbins),log10(meanval)); - %set(ph,'color',col,'linestyle','o','markerfacecolor',col,'markersize',8); - set(ph,'color',col,'linestyle','o','linewidth',2,'markersize',8); - %errorbar(log10(logbins),log10(meanval),log10(meanval+seval)-log10(meanval),log10(meanval-seval)-log10(meanval),'k.'); - - disp(['Loading results for b = ' num2str(b) ]); - %%% uncomment these lines if .mat file is not yet generated. %%% - %typecountrecord= load([ 'outputs/typecountrecordwsjpeak0.0.' num2str(b) '.0.dat']); - %typecountrecordmean = mean(typecountrecord(:,:)); - %save([ 'outputs/typecountrecordmeanwsjpeak0.0.' num2str(b) '.0.mat'],'typecountrecordmean'); - load([ 'outputs/typecountrecordmeanwsjpeak0.0.' num2str(b) '.0.mat']); - - %plot emprical counts with error bars - [logbins meanval seval] = logbinmean(counts,typecountrecordmean,20,20); - ph = plot(log10(logbins),log10(meanval)); - %set(ph,'color',col,'linestyle','^','markerfacecolor',col,'markersize',8); - set(ph,'color',col,'linestyle','^','linewidth',2,'markersize',8); - %errorbar(log10(logbins),log10(meanval),log10(meanval+seval)-log10(meanval),log10(meanval-seval)-log10(meanval),'ko'); - -end - -set(gca,'xtick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'ytick',log10([.1:.1:1 2:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'xlim',[-0.1 3.5]) -set(gca,'ylim',[-.1 2.5]) -set(gca,'FontSize',16) -set(gca,'xticklabel', {'1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -set(gca,'yticklabel', {'0.1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -%title('Chinese restaurant process adaptor') -ylabel('Mean number of lexical entries (tables)') -xlabel('Word frequency (n_w)') -labs = {'Expectation','Empirical, fixed base','Empirical, inferred base'}; -legend(labs,'Location','NorthWest') -box on diff --git a/report/pyp_clustering/acl09-short/code/wsjplots_cl.m b/report/pyp_clustering/acl09-short/code/wsjplots_cl.m deleted file mode 100644 index eed41846..00000000 --- a/report/pyp_clustering/acl09-short/code/wsjplots_cl.m +++ /dev/null @@ -1,99 +0,0 @@ - -load wsj - -figure(1) -clf -subplot(1,2,2) -hold on - -for i = 1:9 - a = i/10; - [logbins predicted dummy] = logbinmean(counts,counts.^a,20,20); - ph = plot(log10(logbins),log10(predicted),'k'); - set(ph,'color',[0.7 0.7 0.7],'linewidth',1.5) -end - -for i = 1:9 - a = i/10; - disp(['Loading results for a = ' num2str(a) ]); - - typecountrecord= load([ 'typecountrecordwsjflat' num2str(a) '.1.0.dat']); - - typecountrecordmean = mean(typecountrecord(500:1000,:)); - - save([ 'typecountrecordmeanwsjflat' num2str(a) '.1.0.mat'],'typecountrecordmean'); - - [logbins meanval seval] = logbinmean(counts,typecountrecordmean,20,20) - errorbar(log10(logbins),log10(meanval),log10(meanval+seval)-log10(meanval),log10(meanval-seval)-log10(meanval),'k.'); - drawnow -end - - - - -[logbins meanval seval] = logbinmean(counts,counts,20,20) -[logbins predicted dummy] = logbinmean(counts,counts,20,20) -ph = plot(log10(logbins),log10(predicted),'r'); -hold on -errorbar(log10(logbins),log10(meanval),log10(meanval+seval)-log10(meanval),log10(meanval-seval)-log10(meanval),'k.'); - -set(ph,'color',[0.7 0.7 0.7],'linewidth',1.5) - -set(gca,'xtick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'ytick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'xlim',[-0.1 3.5]) -set(gca,'ylim',[-0.1 3.5]) -set(gca,'xticklabel', {'1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -set(gca,'yticklabel', {'1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); - -title('Pitman-Yor process adaptor') -ylabel('Mean number of lexical entries') -xlabel('Word frequency (n_w)') -box on - -subplot(1,2,1) - -for i = 1:5 - - b = 10^(i-1) - - disp(['Loading results for b = ' num2str(b) ]); - typecountrecord= load([ 'typecountrecordwsjflat0.0.' num2str(b) '.0.dat']); - - typecountrecordmean = mean(typecountrecord(500:1000,:)); - save([ 'typecountrecordmeanwsjflat0.0.' num2str(b) '.0.mat'],'typecountrecordmean'); - - [logbins meanval seval] = logbinmean(counts,typecountrecordmean,20,20) - [logbins predicted dummy] = logbinmean(counts,crppred(counts,b),20,20) -% errorbar(log10(logbins),meanval,seval,'k.'); - hold on - ph = plot(log10(logbins),log10(predicted),'r'); - % ph = plot(log10(logbins),predicted,'r'); - set(ph,'color',[0.7 0.7 0.7],'linewidth',1.5) - errorbar(log10(logbins),log10(meanval),log10(meanval+seval)-log10(meanval),log10(meanval-seval)-log10(meanval),'k.'); -end - -set(gca,'xtick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'ytick',log10([1:10 20:10:100 200:100:1000 2000:1000:5000])) -set(gca,'xlim',[-0.1 3.5]) -set(gca,'ylim',[-0.1 1.5]) -set(gca,'xticklabel', {'1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -set(gca,'yticklabel', {'1',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', ... - '10',' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '100', ... - ' ', ' ', ' ', ' ', ' ', ' ', ' ', ' ', '1000', ... - ' ', ' ', ' ', ' '}); -title('Chinese restaurant process adaptor') -ylabel('Mean number of lexical entries') -xlabel('Word frequency (n_w)') -box on - - diff --git a/report/pyp_clustering/acl09-short/common-bak/acl-ijcnlp2009.sty b/report/pyp_clustering/acl09-short/common-bak/acl-ijcnlp2009.sty deleted file mode 100644 index 927779a6..00000000 --- a/report/pyp_clustering/acl09-short/common-bak/acl-ijcnlp2009.sty +++ /dev/null @@ -1,368 +0,0 @@ -% File acl-ijcnlp2009.sty -% adapted from -- -% File eacl2006.sty -% September 19, 2005 -% Contact: e.agirre@ehu.es or Sergi.Balari@uab.es - -% This is the LaTeX style file for EACL 2006. It is nearly identical to the -% style files for ACL2005, ACL 2002, ACL 2001, ACL 2000, EACL 95 and EACL -% 99. -% -% Changes made include: adapt layout to A4 and centimeters, widden abstract - -% This is the LaTeX style file for ACL 2000. It is nearly identical to the -% style files for EACL 95 and EACL 99. Minor changes include editing the -% instructions to reflect use of \documentclass rather than \documentstyle -% and removing the white space before the title on the first page -% -- John Chen, June 29, 2000 - -% To convert from submissions prepared using the style file aclsub.sty -% prepared for the ACL 2000 conference, proceed as follows: -% 1) Remove submission-specific information: \whichsession, \id, -% \wordcount, \otherconferences, \area, \keywords -% 2) \summary should be removed. The summary material should come -% after \maketitle and should be in the ``abstract'' environment -% 3) Check all citations. This style should handle citations correctly -% and also allows multiple citations separated by semicolons. -% 4) Check figures and examples. Because the final format is double- -% column, some adjustments may have to be made to fit text in the column -% or to choose full-width (\figure*} figures. -% 5) Change the style reference from aclsub to acl2000, and be sure -% this style file is in your TeX search path - - -% This is the LaTeX style file for EACL-95. It is identical to the -% style file for ANLP '94 except that the margins are adjusted for A4 -% paper. -- abney 13 Dec 94 - -% The ANLP '94 style file is a slightly modified -% version of the style used for AAAI and IJCAI, using some changes -% prepared by Fernando Pereira and others and some minor changes -% by Paul Jacobs. - -% Papers prepared using the aclsub.sty file and acl.bst bibtex style -% should be easily converted to final format using this style. -% (1) Submission information (\wordcount, \subject, and \makeidpage) -% should be removed. -% (2) \summary should be removed. The summary material should come -% after \maketitle and should be in the ``abstract'' environment -% (between \begin{abstract} and \end{abstract}). -% (3) Check all citations. This style should handle citations correctly -% and also allows multiple citations separated by semicolons. -% (4) Check figures and examples. Because the final format is double- -% column, some adjustments may have to be made to fit text in the column -% or to choose full-width (\figure*} figures. - -% Place this in a file called aclap.sty in the TeX search path. -% (Placing it in the same directory as the paper should also work.) - -% Prepared by Peter F. Patel-Schneider, liberally using the ideas of -% other style hackers, including Barbara Beeton. -% This style is NOT guaranteed to work. It is provided in the hope -% that it will make the preparation of papers easier. -% -% There are undoubtably bugs in this style. If you make bug fixes, -% improvements, etc. please let me know. My e-mail address is: -% pfps@research.att.com - -% Papers are to be prepared using the ``acl'' bibliography style, -% as follows: -% \documentclass[11pt]{article} -% \usepackage{acl2000} -% \title{Title} -% \author{Author 1 \and Author 2 \\ Address line \\ Address line \And -% Author 3 \\ Address line \\ Address line} -% \begin{document} -% ... -% \bibliography{bibliography-file} -% \bibliographystyle{acl} -% \end{document} - -% Author information can be set in various styles: -% For several authors from the same institution: -% \author{Author 1 \and ... \and Author n \\ -% Address line \\ ... \\ Address line} -% if the names do not fit well on one line use -% Author 1 \\ {\bf Author 2} \\ ... \\ {\bf Author n} \\ -% For authors from different institutions: -% \author{Author 1 \\ Address line \\ ... \\ Address line -% \And ... \And -% Author n \\ Address line \\ ... \\ Address line} -% To start a seperate ``row'' of authors use \AND, as in -% \author{Author 1 \\ Address line \\ ... \\ Address line -% \AND -% Author 2 \\ Address line \\ ... \\ Address line \And -% Author 3 \\ Address line \\ ... \\ Address line} - -% If the title and author information does not fit in the area allocated, -% place \setlength\titlebox{} right after -% \usepackage{acl2000} -% where can be something larger than 2.25in - -% \typeout{Conference Style for ACL 2000 -- released June 20, 2000} -\typeout{Conference Style for ACL 2005 -- released Octobe 11, 2004} - -% NOTE: Some laser printers have a serious problem printing TeX output. -% These printing devices, commonly known as ``write-white'' laser -% printers, tend to make characters too light. To get around this -% problem, a darker set of fonts must be created for these devices. -% - -%% % Physical page layout - slightly modified from IJCAI by pj -%% \setlength\topmargin{0.0in} \setlength\oddsidemargin{-0.0in} -%% \setlength\textheight{9.0in} \setlength\textwidth{6.5in} -%% \setlength\columnsep{0.2in} -%% \newlength\titlebox -%% \setlength\titlebox{2.25in} -%% \setlength\headheight{0pt} \setlength\headsep{0pt} -%% %\setlength\footheight{0pt} -%% \setlength\footskip{0pt} -%% \thispagestyle{empty} \pagestyle{empty} -%% \flushbottom \twocolumn \sloppy - -%% Original A4 version of page layout -%% \setlength\topmargin{-0.45cm} % changed by Rz -1.4 -%% \setlength\oddsidemargin{.8mm} % was -0cm, changed by Rz -%% \setlength\textheight{23.5cm} -%% \setlength\textwidth{15.8cm} -%% \setlength\columnsep{0.6cm} -%% \newlength\titlebox -%% \setlength\titlebox{2.00in} -%% \setlength\headheight{5pt} -%% \setlength\headsep{0pt} -%% \setlength\footheight{0pt} -%% \setlength\footskip{0pt} -%% \thispagestyle{empty} -%% \pagestyle{empty} - -% A4 modified by Eneko -\setlength{\paperwidth}{21cm} % A4 -\setlength{\paperheight}{29.7cm}% A4 -\setlength\topmargin{-0.5cm} -\setlength\oddsidemargin{0cm} -\setlength\textheight{24.7cm} -\setlength\textwidth{16.0cm} -\setlength\columnsep{0.6cm} -\newlength\titlebox -\setlength\titlebox{2.00in} -\setlength\headheight{5pt} -\setlength\headsep{0pt} -\thispagestyle{empty} -\pagestyle{empty} - - -\flushbottom \twocolumn \sloppy - -% We're never going to need a table of contents, so just flush it to -% save space --- suggested by drstrip@sandia-2 -\def\addcontentsline#1#2#3{} - -% Title stuff, taken from deproc. -\def\maketitle{\par - \begingroup - \def\thefootnote{\fnsymbol{footnote}} - \def\@makefnmark{\hbox to 0pt{$^{\@thefnmark}$\hss}} - \twocolumn[\@maketitle] \@thanks - \endgroup - \setcounter{footnote}{0} - \let\maketitle\relax \let\@maketitle\relax - \gdef\@thanks{}\gdef\@author{}\gdef\@title{}\let\thanks\relax} -\def\@maketitle{\vbox to \titlebox{\hsize\textwidth - \linewidth\hsize \vskip 0.125in minus 0.125in \centering - {\Large\bf \@title \par} \vskip 0.2in plus 1fil minus 0.1in - {\def\and{\unskip\enspace{\rm and}\enspace}% - \def\And{\end{tabular}\hss \egroup \hskip 1in plus 2fil - \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf}% - \def\AND{\end{tabular}\hss\egroup \hfil\hfil\egroup - \vskip 0.25in plus 1fil minus 0.125in - \hbox to \linewidth\bgroup\large \hfil\hfil - \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf} - \hbox to \linewidth\bgroup\large \hfil\hfil - \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf\@author - \end{tabular}\hss\egroup - \hfil\hfil\egroup} - \vskip 0.3in plus 2fil minus 0.1in -}} - -% margins for abstract -\renewenvironment{abstract}% - {\centerline{\large\bf Abstract}% - \begin{list}{}% - {\setlength{\rightmargin}{0.6cm}% - \setlength{\leftmargin}{0.6cm}}% - \item[]\ignorespaces}% - {\unskip\end{list}} - -%\renewenvironment{abstract}{\centerline{\large\bf -% Abstract}\vspace{0.5ex}\begin{quote}}{\par\end{quote}\vskip 1ex} - - -% bibliography - -\def\thebibliography#1{\section*{References} - \global\def\@listi{\leftmargin\leftmargini - \labelwidth\leftmargini \advance\labelwidth-\labelsep - \topsep 1pt plus 2pt minus 1pt - \parsep 0.25ex plus 1pt \itemsep 0.25ex plus 1pt} - \list {[\arabic{enumi}]}{\settowidth\labelwidth{[#1]}\leftmargin\labelwidth - \advance\leftmargin\labelsep\usecounter{enumi}} - \def\newblock{\hskip .11em plus .33em minus -.07em} - \sloppy - \sfcode`\.=1000\relax} - -\def\@up#1{\raise.2ex\hbox{#1}} - -% most of cite format is from aclsub.sty by SMS - -% don't box citations, separate with ; and a space -% also, make the penalty between citations negative: a good place to break -% changed comma back to semicolon pj 2/1/90 -% \def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi -% \def\@citea{}\@cite{\@for\@citeb:=#2\do -% {\@citea\def\@citea{;\penalty\@citeseppen\ }\@ifundefined -% {b@\@citeb}{{\bf ?}\@warning -% {Citation `\@citeb' on page \thepage \space undefined}}% -% {\csname b@\@citeb\endcsname}}}{#1}} - -% don't box citations, separate with ; and a space -% Replaced for multiple citations (pj) -% don't box citations and also add space, semicolon between multiple citations -\def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi - \def\@citea{}\@cite{\@for\@citeb:=#2\do - {\@citea\def\@citea{; }\@ifundefined - {b@\@citeb}{{\bf ?}\@warning - {Citation `\@citeb' on page \thepage \space undefined}}% - {\csname b@\@citeb\endcsname}}}{#1}} - -% Allow short (name-less) citations, when used in -% conjunction with a bibliography style that creates labels like -% \citename{, } -% -\let\@internalcite\cite -\def\cite{\def\citename##1{##1, }\@internalcite} -\def\shortcite{\def\citename##1{}\@internalcite} -\def\newcite{\def\citename##1{{\frenchspacing##1} (}\@internalciteb} - -% Macros for \newcite, which leaves name in running text, and is -% otherwise like \shortcite. -\def\@citexb[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi - \def\@citea{}\@newcite{\@for\@citeb:=#2\do - {\@citea\def\@citea{;\penalty\@m\ }\@ifundefined - {b@\@citeb}{{\bf ?}\@warning - {Citation `\@citeb' on page \thepage \space undefined}}% -{\csname b@\@citeb\endcsname}}}{#1}} -\def\@internalciteb{\@ifnextchar [{\@tempswatrue\@citexb}{\@tempswafalse\@citexb[]}} - -\def\@newcite#1#2{{#1\if@tempswa, #2\fi)}} - -\def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} - -%%% More changes made by SMS (originals in latex.tex) -% Use parentheses instead of square brackets in the text. -\def\@cite#1#2{({#1\if@tempswa , #2\fi})} - -% Don't put a label in the bibliography at all. Just use the unlabeled format -% instead. -\def\thebibliography#1{\vskip\parskip% -\vskip\baselineskip% -\def\baselinestretch{1}% -\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% -\vskip-\parskip% -\vskip-\baselineskip% -\section*{References\@mkboth - {References}{References}}\list - {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} - \setlength{\itemindent}{-\parindent}} - \def\newblock{\hskip .11em plus .33em minus -.07em} - \sloppy\clubpenalty4000\widowpenalty4000 - \sfcode`\.=1000\relax} -\let\endthebibliography=\endlist - -% Allow for a bibliography of sources of attested examples -\def\thesourcebibliography#1{\vskip\parskip% -\vskip\baselineskip% -\def\baselinestretch{1}% -\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% -\vskip-\parskip% -\vskip-\baselineskip% -\section*{Sources of Attested Examples\@mkboth - {Sources of Attested Examples}{Sources of Attested Examples}}\list - {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} - \setlength{\itemindent}{-\parindent}} - \def\newblock{\hskip .11em plus .33em minus -.07em} - \sloppy\clubpenalty4000\widowpenalty4000 - \sfcode`\.=1000\relax} -\let\endthesourcebibliography=\endlist - -\def\@lbibitem[#1]#2{\item[]\if@filesw - { \def\protect##1{\string ##1\space}\immediate - \write\@auxout{\string\bibcite{#2}{#1}}\fi\ignorespaces}} - -\def\@bibitem#1{\item\if@filesw \immediate\write\@auxout - {\string\bibcite{#1}{\the\c@enumi}}\fi\ignorespaces} - -% sections with less space -\def\section{\@startsection {section}{1}{\z@}{-2.0ex plus - -0.5ex minus -.2ex}{1.5ex plus 0.3ex minus .2ex}{\large\bf\raggedright}} -\def\subsection{\@startsection{subsection}{2}{\z@}{-1.8ex plus - -0.5ex minus -.2ex}{0.8ex plus .2ex}{\normalsize\bf\raggedright}} -%% changed by KO to - values to get teh initial parindent right -\def\subsubsection{\@startsection{subsubsection}{3}{\z@}{-1.5ex plus - -0.5ex minus -.2ex}{0.5ex plus .2ex}{\normalsize\bf\raggedright}} -\def\paragraph{\@startsection{paragraph}{4}{\z@}{1.5ex plus - 0.5ex minus .2ex}{-1em}{\normalsize\bf}} -\def\subparagraph{\@startsection{subparagraph}{5}{\parindent}{1.5ex plus - 0.5ex minus .2ex}{-1em}{\normalsize\bf}} - -% Footnotes -\footnotesep 6.65pt % -\skip\footins 9pt plus 4pt minus 2pt -\def\footnoterule{\kern-3pt \hrule width 5pc \kern 2.6pt } -\setcounter{footnote}{0} - -% Lists and paragraphs -\parindent 1em -\topsep 4pt plus 1pt minus 2pt -\partopsep 1pt plus 0.5pt minus 0.5pt -\itemsep 2pt plus 1pt minus 0.5pt -\parsep 2pt plus 1pt minus 0.5pt - -\leftmargin 2em \leftmargini\leftmargin \leftmarginii 2em -\leftmarginiii 1.5em \leftmarginiv 1.0em \leftmarginv .5em \leftmarginvi .5em -\labelwidth\leftmargini\advance\labelwidth-\labelsep \labelsep 5pt - -\def\@listi{\leftmargin\leftmargini} -\def\@listii{\leftmargin\leftmarginii - \labelwidth\leftmarginii\advance\labelwidth-\labelsep - \topsep 2pt plus 1pt minus 0.5pt - \parsep 1pt plus 0.5pt minus 0.5pt - \itemsep \parsep} -\def\@listiii{\leftmargin\leftmarginiii - \labelwidth\leftmarginiii\advance\labelwidth-\labelsep - \topsep 1pt plus 0.5pt minus 0.5pt - \parsep \z@ \partopsep 0.5pt plus 0pt minus 0.5pt - \itemsep \topsep} -\def\@listiv{\leftmargin\leftmarginiv - \labelwidth\leftmarginiv\advance\labelwidth-\labelsep} -\def\@listv{\leftmargin\leftmarginv - \labelwidth\leftmarginv\advance\labelwidth-\labelsep} -\def\@listvi{\leftmargin\leftmarginvi - \labelwidth\leftmarginvi\advance\labelwidth-\labelsep} - -\abovedisplayskip 7pt plus2pt minus5pt% -\belowdisplayskip \abovedisplayskip -\abovedisplayshortskip 0pt plus3pt% -\belowdisplayshortskip 4pt plus3pt minus3pt% - -% Less leading in most fonts (due to the narrow columns) -% The choices were between 1-pt and 1.5-pt leading -\def\@normalsize{\@setsize\normalsize{11pt}\xpt\@xpt} -\def\small{\@setsize\small{10pt}\ixpt\@ixpt} -\def\footnotesize{\@setsize\footnotesize{10pt}\ixpt\@ixpt} -\def\scriptsize{\@setsize\scriptsize{8pt}\viipt\@viipt} -\def\tiny{\@setsize\tiny{7pt}\vipt\@vipt} -\def\large{\@setsize\large{14pt}\xiipt\@xiipt} -\def\Large{\@setsize\Large{16pt}\xivpt\@xivpt} -\def\LARGE{\@setsize\LARGE{20pt}\xviipt\@xviipt} -\def\huge{\@setsize\huge{23pt}\xxpt\@xxpt} -\def\Huge{\@setsize\Huge{28pt}\xxvpt\@xxvpt} diff --git a/report/pyp_clustering/acl09-short/common-bak/acl.bst b/report/pyp_clustering/acl09-short/common-bak/acl.bst deleted file mode 100644 index 4396d4dc..00000000 --- a/report/pyp_clustering/acl09-short/common-bak/acl.bst +++ /dev/null @@ -1,1322 +0,0 @@ - -% BibTeX `acl' style file for BibTeX version 0.99c, LaTeX version 2.09 -% This version was made by modifying `aaai-named' format based on the master -% file by Oren Patashnik (PATASHNIK@SCORE.STANFORD.EDU) - -% Copyright (C) 1985, all rights reserved. -% Modifications Copyright 1988, Peter F. Patel-Schneider -% Further modifictions by Stuart Shieber, 1991, and Fernando Pereira, 1992. -% Copying of this file is authorized only if either -% (1) you make absolutely no changes to your copy, including name, or -% (2) if you do make changes, you name it something other than -% btxbst.doc, plain.bst, unsrt.bst, alpha.bst, and abbrv.bst. -% This restriction helps ensure that all standard styles are identical. - -% There are undoubtably bugs in this style. If you make bug fixes, -% improvements, etc. please let me know. My e-mail address is: -% pfps@spar.slb.com - -% Citation format: [author-last-name, year] -% [author-last-name and author-last-name, year] -% [author-last-name {\em et al.}, year] -% -% Reference list ordering: alphabetical by author or whatever passes -% for author in the absence of one. -% -% This BibTeX style has support for short (year only) citations. This -% is done by having the citations actually look like -% \citename{name-info, }year -% The LaTeX style has to have the following -% \let\@internalcite\cite -% \def\cite{\def\citename##1{##1}\@internalcite} -% \def\shortcite{\def\citename##1{}\@internalcite} -% \def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} -% which makes \shortcite the macro for short citations. - -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% -% Changes made by SMS for thesis style -% no emphasis on "et al." -% "Ph.D." includes periods (not "PhD") -% moved year to immediately after author's name -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% -ENTRY - { address - author - booktitle - chapter - edition - editor - howpublished - institution - journal - key - month - note - number - organization - pages - publisher - school - series - title - type - volume - year - } - {} - { label extra.label sort.label } - -INTEGERS { output.state before.all mid.sentence after.sentence after.block } - -FUNCTION {init.state.consts} -{ #0 'before.all := - #1 'mid.sentence := - #2 'after.sentence := - #3 'after.block := -} - -STRINGS { s t } - -FUNCTION {output.nonnull} -{ 's := - output.state mid.sentence = - { ", " * write$ } - { output.state after.block = - { add.period$ write$ - newline$ - "\newblock " write$ - } - { output.state before.all = - 'write$ - { add.period$ " " * write$ } - if$ - } - if$ - mid.sentence 'output.state := - } - if$ - s -} - -FUNCTION {output} -{ duplicate$ empty$ - 'pop$ - 'output.nonnull - if$ -} - -FUNCTION {output.check} -{ 't := - duplicate$ empty$ - { pop$ "empty " t * " in " * cite$ * warning$ } - 'output.nonnull - if$ -} - -FUNCTION {output.bibitem} -{ newline$ - - "\bibitem[" write$ - label write$ - "]{" write$ - - cite$ write$ - "}" write$ - newline$ - "" - before.all 'output.state := -} - -FUNCTION {fin.entry} -{ add.period$ - write$ - newline$ -} - -FUNCTION {new.block} -{ output.state before.all = - 'skip$ - { after.block 'output.state := } - if$ -} - -FUNCTION {new.sentence} -{ output.state after.block = - 'skip$ - { output.state before.all = - 'skip$ - { after.sentence 'output.state := } - if$ - } - if$ -} - -FUNCTION {not} -{ { #0 } - { #1 } - if$ -} - -FUNCTION {and} -{ 'skip$ - { pop$ #0 } - if$ -} - -FUNCTION {or} -{ { pop$ #1 } - 'skip$ - if$ -} - -FUNCTION {new.block.checka} -{ empty$ - 'skip$ - 'new.block - if$ -} - -FUNCTION {new.block.checkb} -{ empty$ - swap$ empty$ - and - 'skip$ - 'new.block - if$ -} - -FUNCTION {new.sentence.checka} -{ empty$ - 'skip$ - 'new.sentence - if$ -} - -FUNCTION {new.sentence.checkb} -{ empty$ - swap$ empty$ - and - 'skip$ - 'new.sentence - if$ -} - -FUNCTION {field.or.null} -{ duplicate$ empty$ - { pop$ "" } - 'skip$ - if$ -} - -FUNCTION {emphasize} -{ duplicate$ empty$ - { pop$ "" } - { "{\em " swap$ * "}" * } - if$ -} - -INTEGERS { nameptr namesleft numnames } - -FUNCTION {format.names} -{ 's := - #1 'nameptr := - s num.names$ 'numnames := - numnames 'namesleft := - { namesleft #0 > } - - { s nameptr "{ff~}{vv~}{ll}{, jj}" format.name$ 't := - - nameptr #1 > - { namesleft #1 > - { ", " * t * } - { numnames #2 > - { "," * } - 'skip$ - if$ - t "others" = - { " et~al." * } - { " and " * t * } - if$ - } - if$ - } - 't - if$ - nameptr #1 + 'nameptr := - namesleft #1 - 'namesleft := - } - while$ -} - -FUNCTION {format.authors} -{ author empty$ - { "" } - { author format.names } - if$ -} - -FUNCTION {format.editors} -{ editor empty$ - { "" } - { editor format.names - editor num.names$ #1 > - { ", editors" * } - { ", editor" * } - if$ - } - if$ -} - -FUNCTION {format.title} -{ title empty$ - { "" } - - { title "t" change.case$ } - - if$ -} - -FUNCTION {n.dashify} -{ 't := - "" - { t empty$ not } - { t #1 #1 substring$ "-" = - { t #1 #2 substring$ "--" = not - { "--" * - t #2 global.max$ substring$ 't := - } - { { t #1 #1 substring$ "-" = } - { "-" * - t #2 global.max$ substring$ 't := - } - while$ - } - if$ - } - { t #1 #1 substring$ * - t #2 global.max$ substring$ 't := - } - if$ - } - while$ -} - -FUNCTION {format.date} -{ year empty$ - { month empty$ - { "" } - { "there's a month but no year in " cite$ * warning$ - month - } - if$ - } - { month empty$ - { "" } - { month } - if$ - } - if$ -} - -FUNCTION {format.btitle} -{ title emphasize -} - -FUNCTION {tie.or.space.connect} -{ duplicate$ text.length$ #3 < - { "~" } - { " " } - if$ - swap$ * * -} - -FUNCTION {either.or.check} -{ empty$ - 'pop$ - { "can't use both " swap$ * " fields in " * cite$ * warning$ } - if$ -} - -FUNCTION {format.bvolume} -{ volume empty$ - { "" } - { "volume" volume tie.or.space.connect - series empty$ - 'skip$ - { " of " * series emphasize * } - if$ - "volume and number" number either.or.check - } - if$ -} - -FUNCTION {format.number.series} -{ volume empty$ - { number empty$ - { series field.or.null } - { output.state mid.sentence = - { "number" } - { "Number" } - if$ - number tie.or.space.connect - series empty$ - { "there's a number but no series in " cite$ * warning$ } - { " in " * series * } - if$ - } - if$ - } - { "" } - if$ -} - -FUNCTION {format.edition} -{ edition empty$ - { "" } - { output.state mid.sentence = - { edition "l" change.case$ " edition" * } - { edition "t" change.case$ " edition" * } - if$ - } - if$ -} - -INTEGERS { multiresult } - -FUNCTION {multi.page.check} -{ 't := - #0 'multiresult := - { multiresult not - t empty$ not - and - } - { t #1 #1 substring$ - duplicate$ "-" = - swap$ duplicate$ "," = - swap$ "+" = - or or - { #1 'multiresult := } - { t #2 global.max$ substring$ 't := } - if$ - } - while$ - multiresult -} - -FUNCTION {format.pages} -{ pages empty$ - { "" } - { pages multi.page.check - { "pages" pages n.dashify tie.or.space.connect } - { "page" pages tie.or.space.connect } - if$ - } - if$ -} - -FUNCTION {format.year.label} -{ year extra.label * -} - -FUNCTION {format.vol.num.pages} -{ volume field.or.null - number empty$ - 'skip$ - { "(" number * ")" * * - volume empty$ - { "there's a number but no volume in " cite$ * warning$ } - 'skip$ - if$ - } - if$ - pages empty$ - 'skip$ - { duplicate$ empty$ - { pop$ format.pages } - { ":" * pages n.dashify * } - if$ - } - if$ -} - -FUNCTION {format.chapter.pages} -{ chapter empty$ - 'format.pages - { type empty$ - { "chapter" } - { type "l" change.case$ } - if$ - chapter tie.or.space.connect - pages empty$ - 'skip$ - { ", " * format.pages * } - if$ - } - if$ -} - -FUNCTION {format.in.ed.booktitle} -{ booktitle empty$ - { "" } - { editor empty$ - { "In " booktitle emphasize * } - { "In " format.editors * ", " * booktitle emphasize * } - if$ - } - if$ -} - -FUNCTION {empty.misc.check} -{ author empty$ title empty$ howpublished empty$ - month empty$ year empty$ note empty$ - and and and and and - - key empty$ not and - - { "all relevant fields are empty in " cite$ * warning$ } - 'skip$ - if$ -} - -FUNCTION {format.thesis.type} -{ type empty$ - 'skip$ - { pop$ - type "t" change.case$ - } - if$ -} - -FUNCTION {format.tr.number} -{ type empty$ - { "Technical Report" } - 'type - if$ - number empty$ - { "t" change.case$ } - { number tie.or.space.connect } - if$ -} - -FUNCTION {format.article.crossref} -{ key empty$ - { journal empty$ - { "need key or journal for " cite$ * " to crossref " * crossref * - warning$ - "" - } - { "In {\em " journal * "\/}" * } - if$ - } - { "In " key * } - if$ - " \cite{" * crossref * "}" * -} - -FUNCTION {format.crossref.editor} -{ editor #1 "{vv~}{ll}" format.name$ - editor num.names$ duplicate$ - #2 > - { pop$ " et~al." * } - { #2 < - 'skip$ - { editor #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" = - { " et~al." * } - { " and " * editor #2 "{vv~}{ll}" format.name$ * } - if$ - } - if$ - } - if$ -} - -FUNCTION {format.book.crossref} -{ volume empty$ - { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ - "In " - } - { "Volume" volume tie.or.space.connect - " of " * - } - if$ - editor empty$ - editor field.or.null author field.or.null = - or - { key empty$ - { series empty$ - { "need editor, key, or series for " cite$ * " to crossref " * - crossref * warning$ - "" * - } - { "{\em " * series * "\/}" * } - if$ - } - { key * } - if$ - } - { format.crossref.editor * } - if$ - " \cite{" * crossref * "}" * -} - -FUNCTION {format.incoll.inproc.crossref} -{ editor empty$ - editor field.or.null author field.or.null = - or - { key empty$ - { booktitle empty$ - { "need editor, key, or booktitle for " cite$ * " to crossref " * - crossref * warning$ - "" - } - { "In {\em " booktitle * "\/}" * } - if$ - } - { "In " key * } - if$ - } - { "In " format.crossref.editor * } - if$ - " \cite{" * crossref * "}" * -} - -FUNCTION {article} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - crossref missing$ - { journal emphasize "journal" output.check - format.vol.num.pages output - format.date output - } - { format.article.crossref output.nonnull - format.pages output - } - if$ - new.block - note output - fin.entry -} - -FUNCTION {book} -{ output.bibitem - author empty$ - { format.editors "author and editor" output.check } - { format.authors output.nonnull - crossref missing$ - { "author and editor" editor either.or.check } - 'skip$ - if$ - } - if$ - new.block - format.year.label "year" output.check - new.block - format.btitle "title" output.check - crossref missing$ - { format.bvolume output - new.block - format.number.series output - new.sentence - publisher "publisher" output.check - address output - } - { new.block - format.book.crossref output.nonnull - } - if$ - format.edition output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {booklet} -{ output.bibitem - format.authors output - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - howpublished address new.block.checkb - howpublished output - address output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {inbook} -{ output.bibitem - author empty$ - { format.editors "author and editor" output.check } - { format.authors output.nonnull - crossref missing$ - { "author and editor" editor either.or.check } - 'skip$ - if$ - } - if$ - format.year.label "year" output.check - new.block - new.block - format.btitle "title" output.check - crossref missing$ - { format.bvolume output - format.chapter.pages "chapter and pages" output.check - new.block - format.number.series output - new.sentence - publisher "publisher" output.check - address output - } - { format.chapter.pages "chapter and pages" output.check - new.block - format.book.crossref output.nonnull - } - if$ - format.edition output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {incollection} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - crossref missing$ - { format.in.ed.booktitle "booktitle" output.check - format.bvolume output - format.number.series output - format.chapter.pages output - new.sentence - publisher "publisher" output.check - address output - format.edition output - format.date output - } - { format.incoll.inproc.crossref output.nonnull - format.chapter.pages output - } - if$ - new.block - note output - fin.entry -} - -FUNCTION {inproceedings} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - crossref missing$ - { format.in.ed.booktitle "booktitle" output.check - format.bvolume output - format.number.series output - format.pages output - address empty$ - { organization publisher new.sentence.checkb - organization output - publisher output - format.date output - } - { address output.nonnull - format.date output - new.sentence - organization output - publisher output - } - if$ - } - { format.incoll.inproc.crossref output.nonnull - format.pages output - } - if$ - new.block - note output - fin.entry -} - -FUNCTION {conference} { inproceedings } - -FUNCTION {manual} -{ output.bibitem - author empty$ - { organization empty$ - 'skip$ - { organization output.nonnull - address output - } - if$ - } - { format.authors output.nonnull } - if$ - format.year.label "year" output.check - new.block - new.block - format.btitle "title" output.check - author empty$ - { organization empty$ - { address new.block.checka - address output - } - 'skip$ - if$ - } - { organization address new.block.checkb - organization output - address output - } - if$ - format.edition output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {mastersthesis} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - "Master's thesis" format.thesis.type output.nonnull - school "school" output.check - address output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {misc} -{ output.bibitem - format.authors output - new.block - format.year.label output - new.block - title howpublished new.block.checkb - format.title output - howpublished new.block.checka - howpublished output - format.date output - new.block - note output - fin.entry - empty.misc.check -} - -FUNCTION {phdthesis} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.btitle "title" output.check - new.block - "{Ph.D.} thesis" format.thesis.type output.nonnull - school "school" output.check - address output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {proceedings} -{ output.bibitem - editor empty$ - { organization output } - { format.editors output.nonnull } - if$ - new.block - format.year.label "year" output.check - new.block - format.btitle "title" output.check - format.bvolume output - format.number.series output - address empty$ - { editor empty$ - { publisher new.sentence.checka } - { organization publisher new.sentence.checkb - organization output - } - if$ - publisher output - format.date output - } - { address output.nonnull - format.date output - new.sentence - editor empty$ - 'skip$ - { organization output } - if$ - publisher output - } - if$ - new.block - note output - fin.entry -} - -FUNCTION {techreport} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - format.tr.number output.nonnull - institution "institution" output.check - address output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {unpublished} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - note "note" output.check - format.date output - fin.entry -} - -FUNCTION {default.type} { misc } - -MACRO {jan} {"January"} - -MACRO {feb} {"February"} - -MACRO {mar} {"March"} - -MACRO {apr} {"April"} - -MACRO {may} {"May"} - -MACRO {jun} {"June"} - -MACRO {jul} {"July"} - -MACRO {aug} {"August"} - -MACRO {sep} {"September"} - -MACRO {oct} {"October"} - -MACRO {nov} {"November"} - -MACRO {dec} {"December"} - -MACRO {acmcs} {"ACM Computing Surveys"} - -MACRO {acta} {"Acta Informatica"} - -MACRO {cacm} {"Communications of the ACM"} - -MACRO {ibmjrd} {"IBM Journal of Research and Development"} - -MACRO {ibmsj} {"IBM Systems Journal"} - -MACRO {ieeese} {"IEEE Transactions on Software Engineering"} - -MACRO {ieeetc} {"IEEE Transactions on Computers"} - -MACRO {ieeetcad} - {"IEEE Transactions on Computer-Aided Design of Integrated Circuits"} - -MACRO {ipl} {"Information Processing Letters"} - -MACRO {jacm} {"Journal of the ACM"} - -MACRO {jcss} {"Journal of Computer and System Sciences"} - -MACRO {scp} {"Science of Computer Programming"} - -MACRO {sicomp} {"SIAM Journal on Computing"} - -MACRO {tocs} {"ACM Transactions on Computer Systems"} - -MACRO {tods} {"ACM Transactions on Database Systems"} - -MACRO {tog} {"ACM Transactions on Graphics"} - -MACRO {toms} {"ACM Transactions on Mathematical Software"} - -MACRO {toois} {"ACM Transactions on Office Information Systems"} - -MACRO {toplas} {"ACM Transactions on Programming Languages and Systems"} - -MACRO {tcs} {"Theoretical Computer Science"} - -READ - -FUNCTION {sortify} -{ purify$ - "l" change.case$ -} - -INTEGERS { len } - -FUNCTION {chop.word} -{ 's := - 'len := - s #1 len substring$ = - { s len #1 + global.max$ substring$ } - 's - if$ -} - -INTEGERS { et.al.char.used } - -FUNCTION {initialize.et.al.char.used} -{ #0 'et.al.char.used := -} - -EXECUTE {initialize.et.al.char.used} - -FUNCTION {format.lab.names} -{ 's := - s num.names$ 'numnames := - - numnames #1 = - { s #1 "{vv }{ll}" format.name$ } - { numnames #2 = - { s #1 "{vv }{ll }and " format.name$ s #2 "{vv }{ll}" format.name$ * - } - { s #1 "{vv }{ll }\bgroup et al.\egroup " format.name$ } - if$ - } - if$ - -} - -FUNCTION {author.key.label} -{ author empty$ - { key empty$ - - { cite$ #1 #3 substring$ } - - { key #3 text.prefix$ } - if$ - } - { author format.lab.names } - if$ -} - -FUNCTION {author.editor.key.label} -{ author empty$ - { editor empty$ - { key empty$ - - { cite$ #1 #3 substring$ } - - { key #3 text.prefix$ } - if$ - } - { editor format.lab.names } - if$ - } - { author format.lab.names } - if$ -} - -FUNCTION {author.key.organization.label} -{ author empty$ - { key empty$ - { organization empty$ - - { cite$ #1 #3 substring$ } - - { "The " #4 organization chop.word #3 text.prefix$ } - if$ - } - { key #3 text.prefix$ } - if$ - } - { author format.lab.names } - if$ -} - -FUNCTION {editor.key.organization.label} -{ editor empty$ - { key empty$ - { organization empty$ - - { cite$ #1 #3 substring$ } - - { "The " #4 organization chop.word #3 text.prefix$ } - if$ - } - { key #3 text.prefix$ } - if$ - } - { editor format.lab.names } - if$ -} - -FUNCTION {calc.label} -{ type$ "book" = - type$ "inbook" = - or - 'author.editor.key.label - { type$ "proceedings" = - 'editor.key.organization.label - { type$ "manual" = - 'author.key.organization.label - 'author.key.label - if$ - } - if$ - } - if$ - duplicate$ - - "\protect\citename{" swap$ * "}" * - year field.or.null purify$ * - 'label := - year field.or.null purify$ * - - sortify 'sort.label := -} - -FUNCTION {sort.format.names} -{ 's := - #1 'nameptr := - "" - s num.names$ 'numnames := - numnames 'namesleft := - { namesleft #0 > } - { nameptr #1 > - { " " * } - 'skip$ - if$ - - s nameptr "{vv{ } }{ll{ }}{ ff{ }}{ jj{ }}" format.name$ 't := - - nameptr numnames = t "others" = and - { "et al" * } - { t sortify * } - if$ - nameptr #1 + 'nameptr := - namesleft #1 - 'namesleft := - } - while$ -} - -FUNCTION {sort.format.title} -{ 't := - "A " #2 - "An " #3 - "The " #4 t chop.word - chop.word - chop.word - sortify - #1 global.max$ substring$ -} - -FUNCTION {author.sort} -{ author empty$ - { key empty$ - { "to sort, need author or key in " cite$ * warning$ - "" - } - { key sortify } - if$ - } - { author sort.format.names } - if$ -} - -FUNCTION {author.editor.sort} -{ author empty$ - { editor empty$ - { key empty$ - { "to sort, need author, editor, or key in " cite$ * warning$ - "" - } - { key sortify } - if$ - } - { editor sort.format.names } - if$ - } - { author sort.format.names } - if$ -} - -FUNCTION {author.organization.sort} -{ author empty$ - { organization empty$ - { key empty$ - { "to sort, need author, organization, or key in " cite$ * warning$ - "" - } - { key sortify } - if$ - } - { "The " #4 organization chop.word sortify } - if$ - } - { author sort.format.names } - if$ -} - -FUNCTION {editor.organization.sort} -{ editor empty$ - { organization empty$ - { key empty$ - { "to sort, need editor, organization, or key in " cite$ * warning$ - "" - } - { key sortify } - if$ - } - { "The " #4 organization chop.word sortify } - if$ - } - { editor sort.format.names } - if$ -} - -FUNCTION {presort} - -{ calc.label - sort.label - " " - * - type$ "book" = - - type$ "inbook" = - or - 'author.editor.sort - { type$ "proceedings" = - 'editor.organization.sort - { type$ "manual" = - 'author.organization.sort - 'author.sort - if$ - } - if$ - } - if$ - - * - - " " - * - year field.or.null sortify - * - " " - * - title field.or.null - sort.format.title - * - #1 entry.max$ substring$ - 'sort.key$ := -} - -ITERATE {presort} - -SORT - -STRINGS { longest.label last.sort.label next.extra } - -INTEGERS { longest.label.width last.extra.num } - -FUNCTION {initialize.longest.label} -{ "" 'longest.label := - #0 int.to.chr$ 'last.sort.label := - "" 'next.extra := - #0 'longest.label.width := - #0 'last.extra.num := -} - -FUNCTION {forward.pass} -{ last.sort.label sort.label = - { last.extra.num #1 + 'last.extra.num := - last.extra.num int.to.chr$ 'extra.label := - } - { "a" chr.to.int$ 'last.extra.num := - "" 'extra.label := - sort.label 'last.sort.label := - } - if$ -} - -FUNCTION {reverse.pass} -{ next.extra "b" = - { "a" 'extra.label := } - 'skip$ - if$ - label extra.label * 'label := - label width$ longest.label.width > - { label 'longest.label := - label width$ 'longest.label.width := - } - 'skip$ - if$ - extra.label 'next.extra := -} - -EXECUTE {initialize.longest.label} - -ITERATE {forward.pass} - -REVERSE {reverse.pass} - -FUNCTION {begin.bib} - -{ et.al.char.used - { "\newcommand{\etalchar}[1]{$^{#1}$}" write$ newline$ } - 'skip$ - if$ - preamble$ empty$ - - 'skip$ - { preamble$ write$ newline$ } - if$ - - "\begin{thebibliography}{" "}" * write$ newline$ - -} - -EXECUTE {begin.bib} - -EXECUTE {init.state.consts} - -ITERATE {call.type$} - -FUNCTION {end.bib} -{ newline$ - "\end{thebibliography}" write$ newline$ -} - -EXECUTE {end.bib} - diff --git a/report/pyp_clustering/acl09-short/common-bak/acl08.sty b/report/pyp_clustering/acl09-short/common-bak/acl08.sty deleted file mode 100644 index 358f6d27..00000000 --- a/report/pyp_clustering/acl09-short/common-bak/acl08.sty +++ /dev/null @@ -1,344 +0,0 @@ -% File acl2005.sty -% October 11, 2004 -% Contact: oflazer@sabanciuniv.edu - -% This is the LaTeX style file for ACL 2005. It is nearly identical to the -% style files for ACL 2002, ACL 2001, ACL 2000, EACL 95 and EACL -% 99. -% - -% This is the LaTeX style file for ACL 2000. It is nearly identical to the -% style files for EACL 95 and EACL 99. Minor changes include editing the -% instructions to reflect use of \documentclass rather than \documentstyle -% and removing the white space before the title on the first page -% -- John Chen, June 29, 2000 - -% To convert from submissions prepared using the style file aclsub.sty -% prepared for the ACL 2000 conference, proceed as follows: -% 1) Remove submission-specific information: \whichsession, \id, -% \wordcount, \otherconferences, \area, \keywords -% 2) \summary should be removed. The summary material should come -% after \maketitle and should be in the ``abstract'' environment -% 3) Check all citations. This style should handle citations correctly -% and also allows multiple citations separated by semicolons. -% 4) Check figures and examples. Because the final format is double- -% column, some adjustments may have to be made to fit text in the column -% or to choose full-width (\figure*} figures. -% 5) Change the style reference from aclsub to acl2000, and be sure -% this style file is in your TeX search path - - -% This is the LaTeX style file for EACL-95. It is identical to the -% style file for ANLP '94 except that the margins are adjusted for A4 -% paper. -- abney 13 Dec 94 - -% The ANLP '94 style file is a slightly modified -% version of the style used for AAAI and IJCAI, using some changes -% prepared by Fernando Pereira and others and some minor changes -% by Paul Jacobs. - -% Papers prepared using the aclsub.sty file and acl.bst bibtex style -% should be easily converted to final format using this style. -% (1) Submission information (\wordcount, \subject, and \makeidpage) -% should be removed. -% (2) \summary should be removed. The summary material should come -% after \maketitle and should be in the ``abstract'' environment -% (between \begin{abstract} and \end{abstract}). -% (3) Check all citations. This style should handle citations correctly -% and also allows multiple citations separated by semicolons. -% (4) Check figures and examples. Because the final format is double- -% column, some adjustments may have to be made to fit text in the column -% or to choose full-width (\figure*} figures. - -% Place this in a file called aclap.sty in the TeX search path. -% (Placing it in the same directory as the paper should also work.) - -% Prepared by Peter F. Patel-Schneider, liberally using the ideas of -% other style hackers, including Barbara Beeton. -% This style is NOT guaranteed to work. It is provided in the hope -% that it will make the preparation of papers easier. -% -% There are undoubtably bugs in this style. If you make bug fixes, -% improvements, etc. please let me know. My e-mail address is: -% pfps@research.att.com - -% Papers are to be prepared using the ``acl'' bibliography style, -% as follows: -% \documentclass[11pt]{article} -% \usepackage{acl2000} -% \title{Title} -% \author{Author 1 \and Author 2 \\ Address line \\ Address line \And -% Author 3 \\ Address line \\ Address line} -% \begin{document} -% ... -% \bibliography{bibliography-file} -% \bibliographystyle{acl} -% \end{document} - -% Author information can be set in various styles: -% For several authors from the same institution: -% \author{Author 1 \and ... \and Author n \\ -% Address line \\ ... \\ Address line} -% if the names do not fit well on one line use -% Author 1 \\ {\bf Author 2} \\ ... \\ {\bf Author n} \\ -% For authors from different institutions: -% \author{Author 1 \\ Address line \\ ... \\ Address line -% \And ... \And -% Author n \\ Address line \\ ... \\ Address line} -% To start a seperate ``row'' of authors use \AND, as in -% \author{Author 1 \\ Address line \\ ... \\ Address line -% \AND -% Author 2 \\ Address line \\ ... \\ Address line \And -% Author 3 \\ Address line \\ ... \\ Address line} - -% If the title and author information does not fit in the area allocated, -% place \setlength\titlebox{} right after -% \usepackage{acl2000} -% where can be something larger than 2.25in - -% \typeout{Conference Style for ACL 2000 -- released June 20, 2000} -\typeout{Conference Style for ACL 2005 -- released Octobe 11, 2004} - -% NOTE: Some laser printers have a serious problem printing TeX output. -% These printing devices, commonly known as ``write-white'' laser -% printers, tend to make characters too light. To get around this -% problem, a darker set of fonts must be created for these devices. -% - -% Physical page layout - slightly modified from IJCAI by pj -\setlength\topmargin{0.0in} \setlength\oddsidemargin{-0.0in} -\setlength\textheight{9.0in} \setlength\textwidth{6.5in} -\setlength\columnsep{0.2in} -\newlength\titlebox -\setlength\titlebox{2.25in} -\setlength\headheight{0pt} \setlength\headsep{0pt} -%\setlength\footheight{0pt} -\setlength\footskip{0pt} -\thispagestyle{empty} \pagestyle{empty} -\flushbottom \twocolumn \sloppy - -%% A4 version of page layout -%\setlength\topmargin{-0.45cm} % changed by Rz -1.4 -%\setlength\oddsidemargin{.8mm} % was -0cm, changed by Rz -%\setlength\textheight{23.5cm} -%\setlength\textwidth{15.8cm} -%\setlength\columnsep{0.6cm} -%\newlength\titlebox -%\setlength\titlebox{2.00in} -%\setlength\headheight{5pt} -%\setlength\headsep{0pt} -%%\setlength\footheight{0pt} -%\setlength\footskip{0pt} -%\thispagestyle{empty} -%\pagestyle{empty} - -\flushbottom \twocolumn \sloppy - -% We're never going to need a table of contents, so just flush it to -% save space --- suggested by drstrip@sandia-2 -\def\addcontentsline#1#2#3{} - -% Title stuff, taken from deproc. -\def\maketitle{\par - \begingroup - \def\thefootnote{\fnsymbol{footnote}} - \def\@makefnmark{\hbox to 0pt{$^{\@thefnmark}$\hss}} - \twocolumn[\@maketitle] \@thanks - \endgroup - \setcounter{footnote}{0} - \let\maketitle\relax \let\@maketitle\relax - \gdef\@thanks{}\gdef\@author{}\gdef\@title{}\let\thanks\relax} -\def\@maketitle{\vbox to \titlebox{\hsize\textwidth - \linewidth\hsize \vskip 0.125in minus 0.125in \centering - {\Large\bf \@title \par} \vskip 0.2in plus 1fil minus 0.1in - {\def\and{\unskip\enspace{\rm and}\enspace}% - \def\And{\end{tabular}\hss \egroup \hskip 1in plus 2fil - \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf}% - \def\AND{\end{tabular}\hss\egroup \hfil\hfil\egroup - \vskip 0.25in plus 1fil minus 0.125in - \hbox to \linewidth\bgroup\large \hfil\hfil - \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf} - \hbox to \linewidth\bgroup\large \hfil\hfil - \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf\@author - \end{tabular}\hss\egroup - \hfil\hfil\egroup} - \vskip 0.3in plus 2fil minus 0.1in -}} -\renewenvironment{abstract}{\centerline{\large\bf - Abstract}\vspace{0.5ex}\begin{quote} \small}{\par\end{quote}\vskip 1ex} - - -% bibliography - -\def\thebibliography#1{\section*{References} - \global\def\@listi{\leftmargin\leftmargini - \labelwidth\leftmargini \advance\labelwidth-\labelsep - \topsep 1pt plus 2pt minus 1pt - \parsep 0.25ex plus 1pt \itemsep 0.25ex plus 1pt} - \list {[\arabic{enumi}]}{\settowidth\labelwidth{[#1]}\leftmargin\labelwidth - \advance\leftmargin\labelsep\usecounter{enumi}} - \def\newblock{\hskip .11em plus .33em minus -.07em} - \sloppy - \sfcode`\.=1000\relax} - -\def\@up#1{\raise.2ex\hbox{#1}} - -% most of cite format is from aclsub.sty by SMS - -% don't box citations, separate with ; and a space -% also, make the penalty between citations negative: a good place to break -% changed comma back to semicolon pj 2/1/90 -% \def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi -% \def\@citea{}\@cite{\@for\@citeb:=#2\do -% {\@citea\def\@citea{;\penalty\@citeseppen\ }\@ifundefined -% {b@\@citeb}{{\bf ?}\@warning -% {Citation `\@citeb' on page \thepage \space undefined}}% -% {\csname b@\@citeb\endcsname}}}{#1}} - -% don't box citations, separate with ; and a space -% Replaced for multiple citations (pj) -% don't box citations and also add space, semicolon between multiple citations -\def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi - \def\@citea{}\@cite{\@for\@citeb:=#2\do - {\@citea\def\@citea{; }\@ifundefined - {b@\@citeb}{{\bf ?}\@warning - {Citation `\@citeb' on page \thepage \space undefined}}% - {\csname b@\@citeb\endcsname}}}{#1}} - -% Allow short (name-less) citations, when used in -% conjunction with a bibliography style that creates labels like -% \citename{, } -% -\let\@internalcite\cite -\def\cite{\def\citename##1{##1, }\@internalcite} -\def\shortcite{\def\citename##1{}\@internalcite} -\def\newcite{\def\citename##1{{\frenchspacing##1} (}\@internalciteb} - -% Macros for \newcite, which leaves name in running text, and is -% otherwise like \shortcite. -\def\@citexb[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi - \def\@citea{}\@newcite{\@for\@citeb:=#2\do - {\@citea\def\@citea{;\penalty\@m\ }\@ifundefined - {b@\@citeb}{{\bf ?}\@warning - {Citation `\@citeb' on page \thepage \space undefined}}% -{\csname b@\@citeb\endcsname}}}{#1}} -\def\@internalciteb{\@ifnextchar [{\@tempswatrue\@citexb}{\@tempswafalse\@citexb[]}} - -\def\@newcite#1#2{{#1\if@tempswa, #2\fi)}} - -\def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} - -%%% More changes made by SMS (originals in latex.tex) -% Use parentheses instead of square brackets in the text. -\def\@cite#1#2{({#1\if@tempswa , #2\fi})} - -% Don't put a label in the bibliography at all. Just use the unlabeled format -% instead. -\def\thebibliography#1{\small\vskip\parskip% -\vskip\baselineskip% -\def\baselinestretch{1}% -\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% -\vskip-\parskip% -\vskip-\baselineskip% -\section*{References\@mkboth - {References}{References}}\list - {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} - \setlength{\itemsep}{-0.5ex} - \setlength{\itemindent}{-\parindent}} - \def\newblock{\hskip .11em plus .33em minus -.07em} - \sloppy\clubpenalty4000\widowpenalty4000 - \sfcode`\.=1000\relax} -\let\endthebibliography=\endlist - -% Allow for a bibliography of sources of attested examples -\def\thesourcebibliography#1{\vskip\parskip% -\vskip\baselineskip% -\def\baselinestretch{1}% -\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% -\vskip-\parskip% -\vskip-\baselineskip% -\section*{Sources of Attested Examples\@mkboth - {Sources of Attested Examples}{Sources of Attested Examples}}\list - {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} - \setlength{\itemindent}{-\parindent}} - \def\newblock{\hskip .11em plus .33em minus -.07em} - \sloppy\clubpenalty4000\widowpenalty4000 - \sfcode`\.=1000\relax} -\let\endthesourcebibliography=\endlist - -\def\@lbibitem[#1]#2{\item[]\if@filesw - { \def\protect##1{\string ##1\space}\immediate - \write\@auxout{\string\bibcite{#2}{#1}}\fi\ignorespaces}} - -\def\@bibitem#1{\item\if@filesw \immediate\write\@auxout - {\string\bibcite{#1}{\the\c@enumi}}\fi\ignorespaces} - -% sections with less space -\def\section{\@startsection {section}{1}{\z@}{-2.0ex plus - -0.5ex minus -.2ex}{1.5ex plus 0.3ex minus .2ex}{\large\bf\raggedright}} -\def\subsection{\@startsection{subsection}{2}{\z@}{-1.8ex plus - -0.5ex minus -.2ex}{0.8ex plus .2ex}{\normalsize\bf\raggedright}} -\def\subsubsection{\@startsection{subsubsection}{3}{\z@}{1.5ex plus - 0.5ex minus .2ex}{0.5ex plus .2ex}{\normalsize\bf\raggedright}} -\def\paragraph{\@startsection{paragraph}{4}{\z@}{1.5ex plus - 0.5ex minus .2ex}{-1em}{\normalsize\bf}} -\def\subparagraph{\@startsection{subparagraph}{5}{\parindent}{1.5ex plus - 0.5ex minus .2ex}{-1em}{\normalsize\bf}} - -% Footnotes -\footnotesep 6.65pt % -\skip\footins 9pt plus 4pt minus 2pt -\def\footnoterule{\kern-3pt \hrule width 5pc \kern 2.6pt } -\setcounter{footnote}{0} - -% Lists and paragraphs -\parindent 1em -\topsep 4pt plus 1pt minus 2pt -\partopsep 1pt plus 0.5pt minus 0.5pt -\itemsep 2pt plus 1pt minus 0.5pt -\parsep 2pt plus 1pt minus 0.5pt - -\leftmargin 2em \leftmargini\leftmargin \leftmarginii 2em -\leftmarginiii 1.5em \leftmarginiv 1.0em \leftmarginv .5em \leftmarginvi .5em -\labelwidth\leftmargini\advance\labelwidth-\labelsep \labelsep 5pt - -\def\@listi{\leftmargin\leftmargini} -\def\@listii{\leftmargin\leftmarginii - \labelwidth\leftmarginii\advance\labelwidth-\labelsep - \topsep 2pt plus 1pt minus 0.5pt - \parsep 1pt plus 0.5pt minus 0.5pt - \itemsep \parsep} -\def\@listiii{\leftmargin\leftmarginiii - \labelwidth\leftmarginiii\advance\labelwidth-\labelsep - \topsep 1pt plus 0.5pt minus 0.5pt - \parsep \z@ \partopsep 0.5pt plus 0pt minus 0.5pt - \itemsep \topsep} -\def\@listiv{\leftmargin\leftmarginiv - \labelwidth\leftmarginiv\advance\labelwidth-\labelsep} -\def\@listv{\leftmargin\leftmarginv - \labelwidth\leftmarginv\advance\labelwidth-\labelsep} -\def\@listvi{\leftmargin\leftmarginvi - \labelwidth\leftmarginvi\advance\labelwidth-\labelsep} - -\abovedisplayskip 7pt plus2pt minus5pt% -\belowdisplayskip \abovedisplayskip -\abovedisplayshortskip 0pt plus3pt% -\belowdisplayshortskip 4pt plus3pt minus3pt% - -% Less leading in most fonts (due to the narrow columns) -% The choices were between 1-pt and 1.5-pt leading -%\def\@normalsize{\@setsize\normalsize{11pt}\xpt\@xpt} -%\def\small{\@setsize\small{10pt}\ixpt\@ixpt} -%\def\footnotesize{\@setsize\footnotesize{10pt}\ixpt\@ixpt} -%\def\scriptsize{\@setsize\scriptsize{8pt}\viipt\@viipt} -%\def\tiny{\@setsize\tiny{7pt}\vipt\@vipt} -%\def\large{\@setsize\large{14pt}\xiipt\@xiipt} -%\def\Large{\@setsize\Large{16pt}\xivpt\@xivpt} -%\def\LARGE{\@setsize\LARGE{20pt}\xviipt\@xviipt} -%\def\huge{\@setsize\huge{23pt}\xxpt\@xxpt} -%\def\Huge{\@setsize\Huge{28pt}\xxvpt\@xxvpt} - -\let\@@makecaption\@makecaption -\renewcommand{\@makecaption}[1]{\@@makecaption{\small #1}} - -\newcommand{\Thanks}[1]{\thanks{\ #1}} \ No newline at end of file diff --git a/report/pyp_clustering/acl09-short/common-bak/algorithmicx.sty b/report/pyp_clustering/acl09-short/common-bak/algorithmicx.sty deleted file mode 100644 index bfb7daba..00000000 --- a/report/pyp_clustering/acl09-short/common-bak/algorithmicx.sty +++ /dev/null @@ -1,786 +0,0 @@ -% ALGORITHMIC STYLE -- Released 27 APR 2005 -% for LaTeX version 2e -% -% Copyright Szasz Janos -% E-mail szaszjanos@users.sourceforge.net -% -% -% *** INITIALISING *** -% -% -\NeedsTeXFormat{LaTeX2e} -\ProvidesPackage{algorithmicx}[2005/04/27 v1.2 Algorithmicx] -\RequirePackage{ifthen} -\typeout{Document Style algorithmicx 1.2 - a greatly improved `algorithmic' style} -% -\newcounter{ALG@line} -\newcounter{ALG@rem} -\newcounter{ALG@nested} -\newlength{\ALG@tlm} -\newlength{\ALG@thistlm} -\newcounter{ALG@Lnr}% the number of defined languages -\setcounter{ALG@Lnr}{0} -\newcounter{ALG@blocknr}% the number of defined blocks -\setcounter{ALG@blocknr}{0} -\newcounter{ALG@storecount}% number of stored but not restored algorithmic environments -\setcounter{ALG@storecount}{0} -\newcounter{ALG@tmpcounter}% only to decrement things -\newlength\ALG@tmplength% -%\def\algorithmicnoindent{-\ALG@tlm} -% \def\algbackskipbegin{\hskip\ALG@ctlm} -%\def\algbackskip{\hskip-\ALG@thistlm} -%\def\algbackskipend{\hskip-\ALG@tlm} -\def\ALG@defaultindent{\algorithmicindent} -% -% conditional states -% -\def\ALG@newcondstate#1% - {% - \expandafter\edef\csname ALG@x@#1\endcsname% - {\expandafter\noexpand\csname @@ALG@x@#1\endcsname}% - }% -\ALG@newcondstate{notext}% -\ALG@newcondstate{default}% -% -% -% *** ALGORITHMIC *** -% -% -\newcommand\ALG@beginblock[1]% #1 - indentation - {% - \ALG@thistlm\ALG@tlm% - \addtolength\ALG@tlm{#1}% - \addtocounter{ALG@nested}{1}% - \setlength\ALG@tmplength{#1}% - \expandafter\edef\csname ALG@ind@\theALG@nested\endcsname{\the\ALG@tmplength}% - }% -\newcommand\ALG@endblock% - {% - \addtolength\ALG@tlm{-\csname ALG@ind@\theALG@nested\endcsname}% - \addtocounter{ALG@nested}{-1}% - \ALG@thistlm\ALG@tlm% - }% -% -% algorithmic environment -% -\def\ALG@step% - {% - \addtocounter{ALG@line}{1}% - \addtocounter{ALG@rem}{1}% - \ifthenelse{\equal{\arabic{ALG@rem}}{\ALG@numberfreq}}% - {\setcounter{ALG@rem}{0}\alglinenumber{\arabic{ALG@line}}}% - {}% - }% -\newenvironment{algorithmic}[1][0]% - {% - \edef\ALG@numberfreq{#1}% - \def\@currentlabel{\theALG@line}% - % - \setcounter{ALG@line}{0}% - \setcounter{ALG@rem}{0}% - % - \let\\\algbreak% - % - \expandafter\edef\csname ALG@currentblock@\theALG@nested\endcsname{0}% - \expandafter\let\csname ALG@currentlifetime@\theALG@nested\endcsname\relax% - % - \begin{list}% - {\ALG@step}% - {% - \rightmargin\z@% - \itemsep\z@ \itemindent\z@ \listparindent2em% - \partopsep\z@ \parskip\z@ \parsep\z@% - \labelsep 0.5em \topsep 0.2em%\skip 1.2em - \ifthenelse{\equal{#1}{0}}% - {\labelwidth 0.5em}% - {\labelwidth 1.2em}% - \leftmargin\labelwidth \addtolength{\leftmargin}{\labelsep}% Ok. the perfect leftmargin :-)) - \ALG@tlm\z@% - }% - \setcounter{ALG@nested}{0}% - \ALG@beginalgorithmic% - }% - {% end{algorithmic} - % check if all blocks are closed - \ALG@closeloops% - \expandafter\ifnum\csname ALG@currentblock@\theALG@nested\endcsname=0\relax% - \else% - \PackageError{algorithmicx}{Some blocks are not closed!!!}{}% - \fi% - \ALG@endalgorithmic% - \end{list}% - }% -% -% -% *** Functional core *** -% -% -\def\ALG@makeentity#1% execute the entity (#1) - {% - \def\ALG@thisentity{#1}% - \expandafter\ifx\csname ALG@b@\ALG@L @#1@0\endcsname\relax% - \let\ALG@makenobeginrepeat\ALG@makenobegin\ALG@makenobeginrepeat% this entitie ends or continues blocks - \else% - \let\ALG@makebeginrepeat\ALG@makebegin\ALG@makebeginrepeat% this entitie can open blocks - \fi% - \ALG@entitiecommand% - }% -% -\def\ALG@makebegin% executes an entitie that can open blocks - {% - \expandafter\let\expandafter\ALG@thislifetime\csname ALG@currentlifetime@\theALG@nested\endcsname% - \ifx\ALG@thislifetime\relax% - \let\ALG@makebeginrepeat\ALG@doentity% in infinite block I can open my block - \else% - \ifnum\ALG@thislifetime>0\relax% - \ifnum\ALG@thislifetime>65534\else% - \setcounter{ALG@tmpcounter}{\ALG@thislifetime}% the block has 'space' for another included block - \addtocounter{ALG@tmpcounter}{-1}% - \expandafter\edef\csname ALG@currentlifetime@\theALG@nested\endcsname{\arabic{ALG@tmpcounter}}% - \fi% - \let\ALG@makebeginrepeat\ALG@doentity% - \else% the block needs to be closed - \expandafter\ifx\csname ALG@b@\ALG@L @\ALG@thisentity @\csname ALG@currentblock@\theALG@nested\endcsname\endcsname\relax% - \ALG@closebyforce% I can not close this block, continue after it is closed by force -% \ALG@makebegin% - \else% - % the block would be closed automatically, but this entitie can close it, so let's do it with the entity - \let\ALG@makebeginrepeat\ALG@doentity% - \fi% - \fi% - \fi% - \ALG@makebeginrepeat% - }% -% -\def\ALG@makenobegin% executes an entitie that can not open blocks - {% - \expandafter\ifx\csname ALG@currentlifetime@\theALG@nested\endcsname\relax% - \let\ALG@makenobeginrepeat\ALG@doentity% an infinite block must be broken - \else% - \expandafter\ifx\csname ALG@b@\ALG@L @\ALG@thisentity @\csname ALG@currentblock@\theALG@nested\endcsname\endcsname\relax% - \ALG@closebyforce% the block must be ended by force, - \else% - \let\ALG@makenobeginrepeat\ALG@doentity% I can continue / end this block, let's do it - \fi% - \fi% - \ALG@makenobeginrepeat% - }% -% -\def\ALG@dobegin% - {% - \ALG@beginblock{\csname ALG@i@\ALG@L @\ALG@thisentity @\ALG@thisblock\endcsname}% - \expandafter\edef\csname ALG@currentblock@\theALG@nested\endcsname{\csname ALG@b@\ALG@L @\ALG@thisentity @\ALG@thisblock\endcsname}% - \expandafter\ifx\csname ALG@c@\ALG@L @\ALG@thisentity @\ALG@thisblock\endcsname\relax% - \expandafter\let\csname ALG@currentlifetime@\theALG@nested\endcsname\relax% - \else% - \expandafter\edef\csname ALG@currentlifetime@\theALG@nested\endcsname{\csname ALG@c@\ALG@L @\ALG@thisentity @\ALG@thisblock\endcsname}% - \fi% - }% -% -\def\ALG@doend% - {% - \ALG@endblock% - }% -% -\def\ALG@doentity% the number of the closed block, the entitie - {% - \edef\ALG@thisblock{\csname ALG@currentblock@\theALG@nested\endcsname}% - \expandafter\ifx\csname ALG@b@\ALG@L @\ALG@thisentity @\ALG@thisblock\endcsname\relax% - \def\ALG@thisblock{0}% - \fi% - \ALG@getentitytext% - \ifnum\ALG@thisblock=0\else\ALG@doend\fi% - \ifx\ALG@text\ALG@x@notext% - \item[]\nointerlineskip%\vskip-\prevdepth\nointerlineskip% bug: if there are no text and no lines, then this is wrong - \else% - \item% - \fi% - \noindent\hskip\ALG@tlm% - \expandafter\ifnum0=\csname ALG@b@\ALG@L @\ALG@thisentity @\ALG@thisblock\endcsname\else% - \ALG@dobegin% - \fi% - \def\ALG@entitiecommand{\ALG@displayentity}% - }% -% -\def\ALG@getentitytext% - {% - \expandafter\let\expandafter\ALG@text\csname ALG@t@\ALG@L @\ALG@thisentity @\ALG@thisblock\endcsname% - \ifx\ALG@text\ALG@x@default% - % block specific - default - \expandafter\let\expandafter\ALG@text\csname ALG@t@\ALG@L @\ALG@thisentity\endcsname% - \ifx\ALG@text\ALG@x@default% - % block specific - default, language specific - default - \def\ALG@text{\ALG@deftext{\ALG@thisentity}}% - \fi% - \fi% - }% -% -\def\ALG@deftext{\csname ALG@deftext@\ALG@L\endcsname}% -% -\def\ALG@displayentity% - {% - \ifx\ALG@text\ALG@x@notext% - \let\ALG@text\relax% - \fi - \ALG@text% - }% -% -\def\ALG@closebyforce% - {% - \ALG@endblock% - }% -% -\def\ALG@closeloops% closes all finite blocks - {% - \expandafter\ifx\csname ALG@currentlifetime@\theALG@nested\endcsname\relax% - \else% only if it is finite - \ALG@closebyforce% the block must be ended by force, - \ALG@closeloops% the command still runs - \fi% - }% -% -% -% *** Low level block/entitie defining commands *** -% -% -\def\ALG@bl@{0}% the BIG block -\let\ALG@bl@@\ALG@bl@% the BIG block -% -% Create a block -% -\def\ALG@createblock#1% create the block #1, if it does not exists - {% - \@ifundefined{ALG@bl@\ALG@Ld @#1}% needs to be created? - {% - \addtocounter{ALG@blocknr}{1}% increment the block counter - \expandafter\edef\csname ALG@bl@\ALG@Ld @#1\endcsname{\arabic{ALG@blocknr}}% set the block number - }% - {}% - }% -% -% Get the block number -% -\def\ALG@getblocknumber#1{\csname ALG@bl@\ALG@Ld @#1\endcsname}% -% -% Create an entitie -% -\def\ALG@createentitie#1% create the entitie #1, if it does not exists - {% - \expandafter\ALG@edefcmd\csname #1\endcsname{\noexpand\ALG@makeentity{#1}}% - \@ifundefined{ALG@t@\ALG@Ld @#1}% the entity text is defined in this language? - {% - \expandafter\let\csname ALG@t@\ALG@Ld @#1\endcsname\ALG@x@default% - }% - {}% - }% -% -\def\ALG@createtext#1#2% #1 = closed block; #2 = entitie; creates \ALG@t@#2@#1 - {% - \expandafter\let\csname ALG@t@\ALG@Ld @#2@#1\endcsname\ALG@x@default% - }% -% -% End and Continue block -% -\def\ALG@endandcontinueblock#1#2#3#4#5% #1 = new block; #2 = old block; #3 = entitie; #4 = credits; #5 = indent - {% - \ifthenelse{\equal{#3}{}}{}% execute only if the entity is not empty - {% - \ALG@createentitie{#3}% create the entitie - \ALG@createblock{#2}% create the old block, if needed - \ifthenelse{\equal{#1}{}}% whe need to open a new block? - {\expandafter\edef\csname ALG@b@\ALG@Ld @#3@\ALG@getblocknumber{#2}\endcsname{0}}% no, just close the old one - {% yes, - \ALG@createblock{#1}% create the block - \expandafter\edef\csname ALG@b@\ALG@Ld @#3@\ALG@getblocknumber{#2}\endcsname{\ALG@getblocknumber{#1}}% ending the old block opens a new one - \ifthenelse{\equal{#4}{}}% infinite or finite credits? - {\expandafter\let\csname ALG@c@\ALG@Ld @#3@\ALG@getblocknumber{#2}\endcsname\relax}% infinite credits - {\expandafter\edef\csname ALG@c@\ALG@Ld @#3@\ALG@getblocknumber{#2}\endcsname{#4}}% finite credits - \ifthenelse{\equal{#5}{}}% default or specified indentation - {\expandafter\let\csname ALG@i@\ALG@Ld @#3@\ALG@getblocknumber{#2}\endcsname\ALG@defaultindent}% default indentation - {\expandafter\edef\csname ALG@i@\ALG@Ld @#3@\ALG@getblocknumber{#2}\endcsname{#5}}% indentation is specified - }% - \ALG@createtext{\ALG@getblocknumber{#2}}{#3}% - }% - }% -% -% macros used in declarations -% -\def\ALG@p@endtext@E{\algrenewtext{\ALG@v@end}}% -\def\ALG@p@endtext@xE{\algrenewtext[\ALG@v@newblock]{\ALG@v@end}}% -\def\ALG@p@endtext@nE{\algnotext{\ALG@v@end}}% -\def\ALG@p@endtext@xnE{\algnotext[\ALG@v@newblock]{\ALG@v@end}}% -\def\ALG@p@endtext@{}% -% starttext defines are more compex -- care must be taken for the optional parameters -\def\ALG@p@starttext@S{\ALG@p@s@process{\algrenewtext}}% -\def\ALG@p@starttext@C{\ALG@p@s@process{\algrenewtext}}% -\def\ALG@p@starttext@xC{\ALG@p@s@process{\algrenewtext[\ALG@v@oldblock]}}% -\def\ALG@p@s@process#1% - {% - \ifthenelse{\equal{\ALG@v@start}{}}% - {\ALG@p@endtext}% - {\@ifnextchar{[}{\ALG@p@s@getparamcount{#1}}{\ALG@p@s@simple{#1}}}% - }% -\def\ALG@p@s@getparamcount#1[#2]% - {% - \@ifnextchar{[}{\ALG@p@s@getdefparam{#1}{#2}}{\ALG@p@s@param{#1}{#2}}% - }% -\def\ALG@p@s@getdefparam#1#2[#3]% - {% - \ALG@p@s@defparam{#1}{#2}{#3}% - }% -\def\ALG@p@s@simple#1#2{#1{\ALG@v@start}{#2}\ALG@p@endtext}% -\def\ALG@p@s@param#1#2#3{#1{\ALG@v@start}[#2]{#3}\ALG@p@endtext}% -\def\ALG@p@s@defparam#1#2#3#4{#1{\ALG@v@start}[#2][#3]{#4}\ALG@p@endtext}% -% the rest of the crew -\def\ALG@p@starttext@nS{\algnotext{\ALG@v@start}\ALG@p@endtext}% -\def\ALG@p@starttext@nC{\algnotext{\ALG@v@start}\ALG@p@endtext}% -\def\ALG@p@starttext@xnC{\algnotext[\ALG@v@oldblock]{\ALG@v@start}\ALG@p@endtext}% -\def\ALG@p@starttext@{\ALG@p@endtext}% -\def\ALG@p@indent@def#1{\def\ALG@v@indent{#1}\ALG@p@setup}% -\def\ALG@p@indent@{\def\ALG@v@indent{}\ALG@p@setup}% -\def\ALG@p@credits@def#1{\def\ALG@v@credits{#1}\ALG@p@indent}% -\def\ALG@p@credits@{\ALG@p@indent}% -\def\ALG@p@end@def#1{\def\ALG@v@end{#1}\ALG@p@credits}% -\def\ALG@p@end@{\def\ALG@v@end{}\ALG@p@credits}% -\def\ALG@p@start@def#1{\def\ALG@v@start{#1}\ALG@p@end}% -\def\ALG@p@start@{\def\ALG@v@start{}\ALG@p@end}% -\def\ALG@p@oldblock@def#1{\def\ALG@v@oldblock{#1}\ALG@p@start}% -\def\ALG@p@oldblock@{\def\ALG@v@oldblock{}\ALG@p@start}% -\newcommand\ALG@p@newblock[1][]{\def\ALG@v@newblock{#1}\ALG@p@oldblock}% -\def\ALG@p@setup% - {% - \ifthenelse{\equal{\ALG@v@newblock}{}}% - {% - \ifthenelse{\equal{\ALG@v@start}{}}% - {% - \PackageError{algorithmicx}{Block or starting entitie must be specified!!!}{}% - }% - {% - \let\ALG@v@newblock\ALG@v@start% - }% - }% - {% - }% - \ALG@endandcontinueblock% - {\ALG@v@newblock}{\ALG@v@oldblock}{\ALG@v@start}% - {\ALG@v@credits}{\ALG@v@indent}% - \ALG@endandcontinueblock% - {}{\ALG@v@newblock}{\ALG@v@end}% - {}{}% - \ALG@p@starttext% - }% -% -% param handling -% -\newcommand\ALG@p@def[2][def]% - {% - \expandafter\let\csname ALG@p@#2\expandafter\endcsname\csname ALG@p@#2@#1\endcsname% - }% -\def\ALG@p@undef{\ALG@p@def[]}% -% -\def\ALG@p@ons{\ALG@p@def{start}}% -\def\ALG@p@onS{\ALG@p@def{start}\ALG@p@def[S]{starttext}}% -\def\ALG@p@onc{\ALG@p@def{oldblock}\ALG@p@def{start}}% -\def\ALG@p@onC{\ALG@p@def{oldblock}\ALG@p@def{start}\ALG@p@def[C]{starttext}}% -\def\ALG@p@one{\ALG@p@def{end}}% -\def\ALG@p@onE{\ALG@p@def{end}\ALG@p@def[E]{endtext}}% -\def\ALG@p@onxC{\ALG@p@def{oldblock}\ALG@p@def{start}\ALG@p@def[xC]{starttext}}% -\def\ALG@p@onxE{\ALG@p@def{end}\ALG@p@def[xE]{endtext}}% -\def\ALG@p@onnS{\ALG@p@def{start}\ALG@p@def[nS]{starttext}}% -\def\ALG@p@onnC{\ALG@p@def{oldblock}\ALG@p@def{start}\ALG@p@def[nC]{starttext}}% -\def\ALG@p@onnE{\ALG@p@def{end}\ALG@p@def[nE]{endtext}}% -\def\ALG@p@onxnC{\ALG@p@def{oldblock}\ALG@p@def{start}\ALG@p@def[xnC]{starttext}}% -\def\ALG@p@onxnE{\ALG@p@def{end}\ALG@p@def[xnE]{endtext}}% -\def\ALG@p@onb{\def\ALG@v@credits{}}% -\def\ALG@p@onl{\def\ALG@v@credits{1}}% -\def\ALG@p@onL{\ALG@p@def{credits}}% -\def\ALG@p@oni{\ALG@p@def{indent}}% -% -\def\ALG@p@main#1% - {% - \@ifundefined{ALG@ps@\ALG@p@state @#1}% - {% - \csname ALG@ps@\ALG@p@state @other\endcsname{#1}% - }% - {% - \csname ALG@ps@\ALG@p@state @#1\endcsname% - }% - \ALG@p@rec% - }% -% STATE : <> -\expandafter\def\csname ALG@ps@@]\endcsname{\let\ALG@p@rec\relax}% -\def\ALG@ps@@s{\ALG@p@ons}% -\def\ALG@ps@@S{\ALG@p@onS}% -\def\ALG@ps@@c{\ALG@p@onc}% -\def\ALG@ps@@C{\ALG@p@onC}% -\def\ALG@ps@@e{\ALG@p@one}% -\def\ALG@ps@@E{\ALG@p@onE}% -\def\ALG@ps@@N{\typeout{algdef: 'N' obsoloted, use 'nE'.}\ALG@p@onnE}% -\def\ALG@ps@@b{\ALG@p@onb}% -\def\ALG@ps@@l{\ALG@p@onl}% -\def\ALG@ps@@L{\ALG@p@onL}% -\def\ALG@ps@@i{\ALG@p@oni}% -\def\ALG@ps@@x{\def\ALG@p@state{x}}% -\def\ALG@ps@@n{\def\ALG@p@state{n}}% -\def\ALG@ps@@other#1{\typeout{algdef: Ignoring unknown token #1}}% -% STATE : x -\def\ALG@ps@x@C{\def\ALG@p@state{}\ALG@p@onxC}% -\def\ALG@ps@x@E{\def\ALG@p@state{}\ALG@p@onxE}% -\def\ALG@ps@x@N{\def\ALG@p@state{}\typeout{algdef: 'xN' obsoloted, use 'xnE'.}\ALG@p@onxnE}% -\def\ALG@ps@x@n{\def\ALG@p@state{xn}}% -\def\ALG@ps@x@other#1% - {% - \typeout{algdef: Ignoring 'x' before '#1'.}% - \def\ALG@p@state{}% - \def\ALG@p@rec{\let\ALG@p@rec\ALG@p@main\ALG@p@rec#1}% - }% -% STATE : n -\def\ALG@ps@n@S{\def\ALG@p@state{}\ALG@p@onnS}% -\def\ALG@ps@n@C{\def\ALG@p@state{}\ALG@p@onnC}% -\def\ALG@ps@n@E{\def\ALG@p@state{}\ALG@p@onnE}% -\def\ALG@ps@n@x{\def\ALG@p@state{nx}}% -\def\ALG@ps@n@other#1% - {% - \typeout{algdef: Ignoring 'n' before '#1'.}% - \def\ALG@p@state{}% - \def\ALG@p@rec{\let\ALG@p@rec\ALG@p@main\ALG@p@rec#1}% - }% -% STATE : xn -\def\ALG@ps@xn@C{\def\ALG@p@state{}\ALG@p@onxnC}% -\def\ALG@ps@xn@E{\def\ALG@p@state{}\ALG@p@onxnE}% -\def\ALG@ps@xn@x{\typeout{algdef: Ignoring 'x' after 'xn'.}}% -\def\ALG@ps@xn@n{\typeout{algdef: Ignoring 'n' after 'xn'.}}% -\def\ALG@ps@xn@other#1% - {% - \typeout{algdef: Ignoring 'xn' before '#1'.}% - \def\ALG@p@state{}% - \def\ALG@p@rec{\let\ALG@p@rec\ALG@p@main\ALG@p@rec#1}% - }% -% STATE : nx -\def\ALG@ps@nx@C{\def\ALG@p@state{}\ALG@p@onxnC}% -\def\ALG@ps@nx@E{\def\ALG@p@state{}\ALG@p@onxnE}% -\def\ALG@ps@nx@x{\typeout{algdef: Ignoring 'x' after 'nx'.}}% -\def\ALG@ps@nx@n{\typeout{algdef: Ignoring 'n' after 'nx'.}}% -\def\ALG@ps@nx@other#1% - {% - \typeout{algdef: Ignoring 'nx' before '#1'.}% - \def\ALG@p@state{}% - \def\ALG@p@rec{\let\ALG@p@rec\ALG@p@main\ALG@p@rec#1}% - }% -% -% -% *** User level block/entitie commands *** -% -% -% -% algdef{switches}... -- the king of all definitions in the algorithmicx package -% -\newcommand\algdef[1]% - {% - \ALG@p@undef{oldblock}% - \ALG@p@undef{start}% - \ALG@p@undef{end}% - \def\ALG@v@credits{}% - \ALG@p@undef{credits}% - \ALG@p@undef{indent}% - \ALG@p@undef{starttext}% - \ALG@p@undef{endtext}% - \def\ALG@p@state{}% - \let\ALG@p@rec\ALG@p@main% - \ALG@p@rec#1]% - \ALG@p@newblock% - }% -% -% a lot of other macros are provided for convenience -% -\def\algblock{\algdef{se}}% -\def\algcblock{\algdef{ce}}% -\def\algloop{\algdef{sl}}% -\def\algcloop{\algdef{cl}}% -\def\algsetblock{\algdef{seLi}}% -\def\algsetcblock{\algdef{ceLi}}% -\def\algblockx{\algdef{SxE}}% -\def\algblockdefx{\algdef{SE}}% -\def\algcblockx{\algdef{CxE}}% -\def\algcblockdefx{\algdef{CE}}% -\def\algsetblockx{\algdef{SxELi}}% -\def\algsetblockdefx{\algdef{SELi}}% -\def\algsetcblockx{\algdef{CxELi}}% -\def\algsetcblockdefx{\algdef{CELi}}% -\def\algloopdefx{\algdef{Sl}}% -\def\algcloopx{\algdef{xCl}}% -\def\algcloopdefx{\algdef{Cl}}% -% algloopx is not correct, use algloopdefx -% -% Text output commands -% -\newcommand\algrenewtext[2][]% [block]{entity} - {% - \ifthenelse{\equal{#2}{}}{}% - {% - \ifthenelse{\equal{#1}{}}% - {% - \expandafter\let\csname ALG@t@\ALG@Ld @#2\endcsname\relax% - \expandafter\newcommand\csname ALG@t@\ALG@Ld @#2\endcsname% - }% - {% - \expandafter\let\csname ALG@t@\ALG@Ld @#2@\ALG@getblocknumber{#1}\endcsname\relax% - \expandafter\newcommand\csname ALG@t@\ALG@Ld @#2@\ALG@getblocknumber{#1}\endcsname% - }% - }% - }% -% -\def\ALG@letentitytext#1#2% [block]{entity} - {% - \ifthenelse{\equal{#2}{}}{}% - {% - \ifthenelse{\equal{#1}{}}% - {% - \expandafter\let\csname ALG@t@\ALG@Ld @#2\endcsname% - }% - {% - \expandafter\let\csname ALG@t@\ALG@Ld @#2@\ALG@getblocknumber{#1}\endcsname% - }% - }% - }% -% -\newcommand\algnotext[2][]% [block]{entity} - {% - \ALG@letentitytext{#1}{#2}\ALG@x@notext% - }% -% -\newcommand\algdefaulttext[2][]% [block]{entity} - {% - \ALG@letentitytext{#1}{#2}\ALG@x@default% - }% -% -\def\ALG@notext*{\algnotext}% -\def\algtext{\@ifnextchar{*}{\ALG@notext}{\algrenewtext}}% -% -% -% *** LANGUAGE SWITCHING *** -% -% -% -\newcommand\algnewlanguage[1]% - {% - \@ifundefined{ALG@L@#1}% needs to be created? - {}% - {% - \PackageError{algorithmicx}{Language '#1' already defined!}{}% - }% - \addtocounter{ALG@Lnr}{1}% increment the language counter - \expandafter\edef\csname ALG@L@#1\endcsname{\arabic{ALG@Lnr}}% set the language number - \edef\ALG@Ld{\csname ALG@L@#1\endcsname}% - \expandafter\let\csname ALG@bl@\ALG@Ld @\endcsname\ALG@bl@% the BIG block - \expandafter\let\csname ALG@bl@\ALG@Ld @@\endcsname\ALG@bl@% the BIG block - \algdef{SL}[STATE]{State}{0}{}% - \expandafter\def\csname ALG@deftext@\ALG@Ld\endcsname{\textbf}% - \algnewcommand\algorithmiccomment[1]{\hfill\(\triangleright\) ##1}% - \algnewcommand\algorithmicindent{1.5em}% - \algnewcommand\alglinenumber[1]{\footnotesize ##1:}% - \algnewcommand\ALG@beginalgorithmic\relax% for user overrides - \algnewcommand\ALG@endalgorithmic\relax% for user overrides - }% -% -\newcommand\algsetlanguage[1]% - {% - \@ifundefined{ALG@L@#1}% needs to be created? - {% - \PackageError{algorithmicx}{Language '#1' is not yet defined!}{}% - }{}% - \edef\ALG@L{\csname ALG@L@#1\endcsname}% - }% -% -\newcommand\algdeflanguage[1]% - {% - \@ifundefined{ALG@L@#1}% needs to be created? - {% - \PackageError{algorithmicx}{Language '#1' is not yet defined!}{}% - }{}% - \edef\ALG@Ld{\csname ALG@L@#1\endcsname}% - }% -% -\newcommand\alglanguage[1]% - {% - \algdeflanguage{#1}% - \algsetlanguage{#1}% - }% -% -% -% *** Defining language dependent stuff *** -% -% -\def\ALG@eatoneparam#1{}% -\def\ALG@defbasecmd#1#2% - {% - \edef\ALG@tmp{\expandafter\ALG@eatoneparam\string #2}% - \@ifundefined\ALG@tmp{\edef #2{\noexpand\csname ALG@cmd@\noexpand\ALG@L @\ALG@tmp\endcsname}}{}% - \expandafter#1\csname ALG@cmd@\ALG@Ld @\ALG@tmp\endcsname% - }% -\newcommand\algnewcommand{\ALG@defbasecmd\newcommand}% -\newcommand\algrenewcommand{\ALG@defbasecmd\renewcommand}% -\def\ALG@letcmd{\ALG@defbasecmd\let}% -\def\ALG@defcmd{\ALG@defbasecmd\def}% -\def\ALG@edefcmd{\ALG@defbasecmd\edef}% -% -% -% *** OTHERS *** -% -% -\def\BState{\State \algbackskip}% -\def\Statex{\item[]}% an empty line -\newcommand\algrenewcomment{\algrenewcommand\algorithmiccomment}% -\def\Comment{\algorithmiccomment}% -\def\algref#1#2{\ref{#1}.\ref{#2}}% -\algnewlanguage{default}% -\algsetlanguage{default}% -% -% -% *** Line breaks *** -% -% -\newcommand\algbreak% for multiline parameters !!! needs fix - {% - \item% -% \hskip\ALG@parindent%!!! not yet implemented -% \hskip-\algorithmicindent% - }% -% -\def\ALG@noputindents% - {% - \hskip\ALG@tlm% - }% -% -% -% *** algorithm store / restore *** -% -% -% store -% -\ALG@newcondstate{mustrestore}% -\def\algstore% - {% - \renewcommand\ALG@beginblock% - {% - \PackageError{algorithmicx}{The environment must be closed after store!}{}% - }% - \@ifstar{\ALG@starstore}{\ALG@nostarstore}% - }% -\def\ALG@nostarstore#1% save all infos into #1 and terminate the algorithmic block - {% - \addtocounter{ALG@storecount}{1}% - \expandafter\global\expandafter\let\csname ALG@save@mustrestore@#1\endcsname\ALG@x@mustrestore% - \ALG@starstore{#1}% - }% -\def\ALG@starstore#1% - {% - \@ifundefined{ALG@save@line@#1}{}% - {\PackageError{algorithmicx}{This save name '#1' is already used!}{}}% - \def\ALG@savename{#1}% - \expandafter\xdef\csname ALG@save@totalnr@\ALG@savename\endcsname{\theALG@nested}% - \expandafter\xdef\csname ALG@save@line@\ALG@savename\endcsname{\theALG@line}% - \expandafter\xdef\csname ALG@save@numberfreq@\ALG@savename\endcsname{\ALG@numberfreq}% - \expandafter\xdef\csname ALG@save@rem@\ALG@savename\endcsname{\theALG@rem}% - \let\ALG@storerepeat\ALG@store% - \ALG@storerepeat% - }% -\def\ALG@store% simply terminate all open blocks - {% - \ifnum\theALG@nested=0\let\ALG@storerepeat\relax% - \else% - \expandafter\xdef\csname ALG@save@currentblock@\ALG@savename @\theALG@nested\endcsname% - {\csname ALG@currentblock@\theALG@nested\endcsname}% - \expandafter\ifx\csname ALG@currentlifetime@\theALG@nested\endcsname\relax% - \else% - \expandafter\xdef\csname ALG@save@currentlifetime@\ALG@savename @\theALG@nested\endcsname% - {\csname ALG@currentlifetime@\theALG@nested\endcsname}% - \fi% - \expandafter\xdef\csname ALG@save@ind@\ALG@savename @\theALG@nested\endcsname% - {\csname ALG@ind@\theALG@nested\endcsname}% - \ALG@closebyforce% - \fi% - \ALG@storerepeat% - }% -% -% restore -% -\def\algrestore% - {% - \@ifstar{\ALG@starrestore}{\ALG@nostarrestore}% - }% -\def\ALG@starrestore% - {% - \let\ALG@restorerem\relax% - \let\ALG@restorereprem\relax% - \ALG@restoremain% - }% -\def\ALG@nostarrestore% - {% - \let\ALG@restorerem\ALG@restoreremovesave% - \let\ALG@restorereprem\ALG@restorerepremovesave% - \ALG@restoremain% - }% -\def\ALG@restoreremovesave% - {% - \expandafter\global\expandafter\let\csname ALG@save@totalnr@\ALG@savename\endcsname\relax% - \expandafter\global\expandafter\let\csname ALG@save@line@\ALG@savename\endcsname\relax% - \expandafter\global\expandafter\let\csname ALG@save@rem@\ALG@savename\endcsname\relax% - \expandafter\global\expandafter\let\csname ALG@save@totalnr@\ALG@savename\endcsname\relax% - \expandafter\global\expandafter\let\csname ALG@save@numberfreq@\ALG@savename\endcsname\relax% - }% -\def\ALG@restorerepremovesave% - {% - \expandafter\global\expandafter\let\csname ALG@save@currentblock@\ALG@savename @\theALG@tmpcounter\endcsname\relax% - \expandafter\global\expandafter\let\csname ALG@save@currentlifetime@\ALG@savename @\theALG@tmpcounter\endcsname\relax% - \expandafter\global\expandafter\let\csname ALG@save@currentlifetime@\ALG@savename @\theALG@tmpcounter\endcsname\relax% - \expandafter\global\expandafter\let\csname ALG@save@ind@\ALG@savename @\theALG@tmpcounter\endcsname\relax% - }% -\def\ALG@restoremain#1% restore all infos from #1 in an open algorithmic block - {% - \ifnum\theALG@line=0% - \else\PackageError{algorithmicx}{Restore might be used only at the beginning of the environment!}{}% - \fi% - \def\ALG@savename{#1}% - \expandafter\ifx\csname ALG@save@totalnr@\ALG@savename\endcsname\relax% - \PackageError{algorithmicx}{Save '\ALG@savename'\space not defined!!!}{}% - \fi% - \@ifundefined{ALG@save@mustrestore@\ALG@savename}{}% - {% - \addtocounter{ALG@storecount}{-1}% - \expandafter\global\expandafter\let\csname ALG@save@mustrestore@\ALG@savename\endcsname\relax% - }% - \setcounter{ALG@line}{\csname ALG@save@line@\ALG@savename\endcsname}% - \edef\ALG@numberfreq{\csname ALG@save@numberfreq@\ALG@savename\endcsname}% - \setcounter{ALG@rem}{\csname ALG@save@rem@\ALG@savename\endcsname}% - \setcounter{ALG@tmpcounter}{\csname ALG@save@totalnr@\ALG@savename\endcsname}% - \setcounter{ALG@nested}{0}% - \ALG@restorerem% - \let\ALG@restorerepeat\ALG@restore% - \ALG@restorerepeat% - }% -\def\ALG@restore% - {% - \ifnum\theALG@tmpcounter>0% - \expandafter\edef\csname ALG@currentblock@\theALG@tmpcounter\endcsname% - {\csname ALG@save@currentblock@\ALG@savename @\theALG@tmpcounter\endcsname}% - \expandafter\ifx\csname ALG@save@currentlifetime@\ALG@savename @\theALG@tmpcounter\endcsname\relax% - \expandafter\let\csname ALG@currentlifetime@\theALG@tmpcounter\endcsname\relax% - \else% - \expandafter\edef\csname ALG@currentlifetime@\theALG@tmpcounter\endcsname% - {\csname ALG@save@currentlifetime@\ALG@savename @\theALG@tmpcounter\endcsname}% - \fi% - % - \ALG@beginblock{\csname ALG@save@ind@\ALG@savename @\theALG@tmpcounter\endcsname}% - \ALG@restorereprem% - \addtocounter{ALG@tmpcounter}{-1}% - \else\let\ALG@restorerepeat\relax% - \fi% - \ALG@restorerepeat% - }% -\AtEndDocument% - {% - \ifnum\theALG@storecount>0\relax% - \PackageError{algorithmicx}{Some stored algorithms are not restored!}{}% - \fi% - }% diff --git a/report/pyp_clustering/acl09-short/common-bak/algpseudocode.sty b/report/pyp_clustering/acl09-short/common-bak/algpseudocode.sty deleted file mode 100644 index fca966ac..00000000 --- a/report/pyp_clustering/acl09-short/common-bak/algpseudocode.sty +++ /dev/null @@ -1,92 +0,0 @@ -% PSEUDOCODE ALGORITHMIC STYLE -- Released 27 APR 2005 -% for LaTeX version 2e -% -% Copyright Szasz Janos -% E-mail szaszjanos@users.sourceforge.net -% Based on Peter Williams's algorithmic.sty -% -\NeedsTeXFormat{LaTeX2e}% -\ProvidesPackage{algpseudocode}% -\RequirePackage{ifthen}% -\RequirePackage{algorithmicx}% -\typeout{Document Style - pseudocode environments for use with the `algorithmicx' style}% -% -\def\ALG@noend{f}% -\newboolean{ALG@compatible}% -\setboolean{ALG@compatible}{false}% -% -\DeclareOption{noend}{\def\ALG@noend{t}}% -\DeclareOption{end}{\def\ALG@noend{f}}% -\DeclareOption{compatible}{\typeout{For compatibility mode use algcompatible.sty!!!}\setboolean{ALG@compatible}{true}}% -\DeclareOption{noncompatible}{\setboolean{ALG@noncompatible}{false}}% -\ProcessOptions% -% -% *** DECLARATIONS *** -% -\algnewlanguage{pseudocode}% -\alglanguage{pseudocode}% -% -% *** KEYWORDS *** -% -\algnewcommand\algorithmicend{\textbf{end}} -\algnewcommand\algorithmicdo{\textbf{do}} -\algnewcommand\algorithmicwhile{\textbf{while}} -\algnewcommand\algorithmicfor{\textbf{for}} -\algnewcommand\algorithmicforall{\textbf{for all}} -\algnewcommand\algorithmicloop{\textbf{loop}} -\algnewcommand\algorithmicrepeat{\textbf{repeat}} -\algnewcommand\algorithmicuntil{\textbf{until}} -\algnewcommand\algorithmicprocedure{\textbf{procedure}} -\algnewcommand\algorithmicfunction{\textbf{function}} -\algnewcommand\algorithmicif{\textbf{if}} -\algnewcommand\algorithmicthen{\textbf{then}} -\algnewcommand\algorithmicelse{\textbf{else}} -\algnewcommand\algorithmicrequire{\textbf{Require:}} -\algnewcommand\algorithmicensure{\textbf{Ensure:}} -\algnewcommand\algorithmicreturn{\textbf{return}} -\algnewcommand\textproc{\textsc} -% -% *** DECLARED LOOPS *** -% -\algdef{SE}[WHILE]{While}{EndWhile}[1]{\algorithmicwhile\ #1\ \algorithmicdo}{\algorithmicend\ \algorithmicwhile}% -\algdef{SE}[FOR]{For}{EndFor}[1]{\algorithmicfor\ #1\ \algorithmicdo}{\algorithmicend\ \algorithmicfor}% -\algdef{S}[FOR]{ForAll}[1]{\algorithmicforall\ #1\ \algorithmicdo}% -\algdef{SE}[LOOP]{Loop}{EndLoop}{\algorithmicloop}{\algorithmicend\ \algorithmicloop}% -\algdef{SE}[REPEAT]{Repeat}{Until}{\algorithmicrepeat}[1]{\algorithmicuntil\ #1}% -\algdef{SE}[IF]{If}{EndIf}[1]{\algorithmicif\ #1\ \algorithmicthen}{\algorithmicend\ \algorithmicif}% -\algdef{C}[IF]{IF}{ElsIf}[1]{\algorithmicelse\ \algorithmicif\ #1\ \algorithmicthen}% -\algdef{Ce}[ELSE]{IF}{Else}{EndIf}{\algorithmicelse}% -\algdef{SE}[PROCEDURE]{Procedure}{EndProcedure}% - [2]{\algorithmicprocedure\ \textproc{#1}\ifthenelse{\equal{#2}{}}{}{(#2)}}% - {\algorithmicend\ \algorithmicprocedure}% -\algdef{SE}[FUNCTION]{Function}{EndFunction}% - [2]{\algorithmicfunction\ \textproc{#1}\ifthenelse{\equal{#2}{}}{}{(#2)}}% - {\algorithmicend\ \algorithmicfunction}% -% -\ifthenelse{\equal{\ALG@noend}{t}}% - {% - \algtext*{EndWhile}% - \algtext*{EndFor}% - \algtext*{EndLoop}% - \algtext*{EndIf}% - \algtext*{EndProcedure}% - \algtext*{EndFunction}% - }{}% -% -% *** OTHER DECLARATIONS *** -% -\algnewcommand\Require{\item[\algorithmicrequire]}% -\algnewcommand\Ensure{\item[\algorithmicensure]}% -\algnewcommand\Return{\algorithmicreturn{} }% -\algnewcommand\Call[2]{\textproc{#1}\ifthenelse{\equal{#2}{}}{}{(#2)}}% -% -% -% -\ifthenelse{\boolean{ALG@compatible}}% - {% - \ifthenelse{\equal{\ALG@noend}{t}}% - {\RequirePackage[noend]{algcompatible}}% - {\RequirePackage{algcompatible}}% - }% - {}% -% diff --git a/report/pyp_clustering/acl09-short/common-bak/hyphen.sty b/report/pyp_clustering/acl09-short/common-bak/hyphen.sty deleted file mode 100644 index 028e8fb1..00000000 --- a/report/pyp_clustering/acl09-short/common-bak/hyphen.sty +++ /dev/null @@ -1,23 +0,0 @@ -%%%%%%%%% HYPHENATION CONTROL %%%%%%%% - -\pretolerance 250 -\tolerance 500 -% \hyphenpenalty 250 -\hyphenpenalty 200 -\exhyphenpenalty 100 -\doublehyphendemerits 7500 -\finalhyphendemerits 7500 -\brokenpenalty 10000 -\lefthyphenmin 3 -\righthyphenmin 3 -\widowpenalty 10000 -\clubpenalty 10000 -\displaywidowpenalty 10000 -\looseness 1 - -\hyphenation{phon-emic} -\hyphenation{Cam-er-oon} -\hyphenation{Kam-erun} -\hyphenation{ex-am-ple} -\hyphenation{para-digm} -\hyphenation{para-digms} diff --git a/report/pyp_clustering/acl09-short/common-bak/jeffe.sty b/report/pyp_clustering/acl09-short/common-bak/jeffe.sty deleted file mode 100644 index d2cd2e99..00000000 --- a/report/pyp_clustering/acl09-short/common-bak/jeffe.sty +++ /dev/null @@ -1,566 +0,0 @@ -% ============================-*- LaTeX -*-============================= -% -% jeffe.sty -- macros I use everywhere -% -% Jeff Erickson (jeffe@cs.uiuc.edu) -% Last modified 09 Jul 2000 -% This is free; caveat emptor! -% -% Requirements that may not be part of every TeX distribution: -% (1) The standard AMS math packages amsmath and amssymb. These are -% absolutely vital to anyone who typesets mathematics of any -% kind. If you don't have them, get them NOW!! -% (2) The textcomp package. Cosmetic only. -% (3) Knuth's manual font `manfnt'. Cosmetic only. -% -% ====================================================================== -\RequirePackage{latexsym,amsmath,amssymb} - -\hyphenation{co-or-din-ate co-or-din-ates half-space stereo-iso-mers -stereo-iso-mer Round-table} - -% ---------------------------------------------------------------------- -% Common abbreviations and words with accents -% ---------------------------------------------------------------------- - -% ---- LATIN ---- -\def\etal{\emph{et~al.}} -\def\ie{\emph{i.e.}} -\def\eg{\emph{e.g.}} -\def\vitae{vit\ae{}} -\def\apriori{\emph{a~priori}} -\def\aposteriori{\emph{a~posteriori}} - -% ---- FRENCH ---- -\def\naive{na\"{\i}ve} -\def\Naive{Na\"{\i}ve} -\def\naively{na\"{\i}vely} % Okay, I know, this isn't French. -\def\Naively{Na\"{\i}vely} -\def\cafe{caf\'e} - -% ---- GERMAN ---- -\def\fur{f\"ur} -\def\Universitat{Universit\"at} -\def\Saarbrucken{Saar\-br\"ucken} % Bypass TeX hyphenation -\def\Zurich{Z\"urich} - -% ---- PORTUGESE (Hi Jorge!) ---- -\def\Computacao{Computa\c{c}\~ao} - -% ---- PROPER NAMES (because I'm lazy) ---- -\def\Benes{Bene\v{s}} % ...network -\def\Bezier{B\'ezier} % ...spline/curve/surface -\def\Bjorner{Bj\"orner} -\def\Bochis{Bochi\c{s}} % Daciana -\def\Boruvka{Bor\.uvka} % ...'s MST algorithm -\def\Bragger{Br\"agger} -\def\Bronnimann{Br\"onnimann} \def\Herve{Herv\'e} -\def\Bruckner{Br\"uckner} -\def\Caratheodory{Carath\'eodory} % Constantin -\def\Chvatal{Chv\'atal} \def\Vasek{Va\v{s}ek} - \def\Joao{Jo\~ao} % Compa -\def\Cortes{Cort\'es} % Carmen -\def\Dujmovic{Dujmovi\'c} % Vida - \def\Fredo{Fr\'edo} % Durand -\def\Erdos{Erd\H{o}s} \def\Pal{P\'al} -\def\Furedi{F\"uredi} \def\Zoltan{Zolt\'an} -\def\Grobner{Gr\"obner} % ... basis -\def\Grunbaum{Gr\"unbaum} % Branko -\def\Hanoi{Hano\"\i} % Tower of... -\def\Jarnik{Jarn\a'{\i}k} % ...'s (`Prim's') MST algorithm -\def\Komlos{Koml\'os} -\def\Kovari{K\"ov\'ari} -\def\Lovasz{Lov\'asz} \def\Laszlo{L\'aszl\'o} -\def\Matousek{Matou\v{s}ek} \def\Jiri{Ji\v{r}\'\i} -\def\Mnev{Mn\"ev} -\def\Mobius{M\"obius} % ... strip/transformation/function -\def\Mucke{M\"ucke} % Ernst -\def\ODunliang{\'O'D\'unliang} -\def\Oleinik{Ole\u{\i}nik} - \def\Janos{J\'anos} % Pach -\def\Palasti{Pal\'asti} - \def\Belen{Bel\'en} % Palop -\def\Petrovskii{Petrovski\u{\i}} -\def\Pinar{P\i nar} % Ali -\def\Plucker{Pl\"ucker} % ... coordinates -\def\Poincare{Poincar\'e} % ... duality/halfplane - \def\Gunter{G\"unter} % Rote, Ziegler -\def\Sacristan{Sacrist\'an} % Vera -\def\Saskin{\v{S}a\v{s}kin} -\def\Schomer{Sch\"omer} -\def\Schonhardt{Sch\"onhardt} % ... polyhedron -\def\Sos{S\'os} -\def\Stackel{St\"ackel} % Paul -\def\Szekely{Sz\'ekely} -\def\Szemeredi{Szemer\'edi} -\def\Toth{T\'{o}th} % Geza -\def\Turan{Tur\'an} -\def\Ungor{\"Ung\"or} % Alper -\def\Voronoi{Vorono\"i} % ... diagram [for francophile pedants only] - -% Other -\def\Cplusplus{C\raisebox{0.5ex}{\tiny\bf++}} - -% ---------------------------------------------------------------------- -% Simple math stuff -% ---------------------------------------------------------------------- - -% ---- SYMBOLS ---- -\let\e\varepsilon % a ``real'' epsilon - -\def\Integer{\mathsf{Z\hspace{-0.4em}Z}} -\def\Natural{\mathrm{I\!N}} -\def\Real{\mathrm{I\!R}} -\def\Proj{\mathrm{I\!P}} % projective space -\def\Hyper{\mathrm{I\!H}} % hyperbolic space - -% -% These two look okay in Computer Modern 11pt, or Concrete Roman -% 12pt, but they need serious work in other sizes. I need to figure -% out how to draw a vertical bar, or better yet a shallow arc, inside -% the bowls. Or maybe I need to learn METAFONT. -% -\def\Complex{\mathrm{\,\raise 0.33ex\hbox{\scriptsize\bf(}\!\!\!C}} -\def\Rational{\mathrm{\,\raise 0.33ex\hbox{\scriptsize\bf(}\!\!\!Q}} - -% -% Here are more standard, but uglier, versions of these symbols. -% They stick out, because they're all in Times Roman Bold Outline! -% I *really* want a Concrete Blackboard or Euler Blackboard font, but -% I'd settle for Computer Modern Blackboard. -% -%\def\Real{\mathbb{R}} -%\def\Proj{\mathbb{P}} -%\def\Hyper{\mathbb{H}} -%\def\Integer{\mathbb{Z}} -%\def\Natural{\mathbb{N}} -%\def\Complex{\mathbb{C}} -%\def\Rational{\mathbb{Q}} - -\let\N\Natural -\let\Q\Rational -\let\R\Real -\let\Z\Integer -\def\Rd{\Real^d} -\def\RP{\Real\Proj} -\def\CP{\Complex\Proj} - -% ---- OPERATORS (requires amsmath) ---- -\def\aff{\operatorname{aff}} % (\Line is better!) -\def\area{\operatorname{area}} -\def\argmax{\operatornamewithlimits{arg\,max}} -\def\argmin{\operatornamewithlimits{arg\,min}} -\def\Aut{\operatorname{Aut}} % Automorphism group -\def\card{\operatorname{card}} % cardinality, deprecated for \abs -\def\conv{\operatorname{conv}} % (\overline is better!) -\def\E{\operatorname{E}} % Expectation: $\E[X]$ (like \Pr) -\def\EE{\operatornamewithlimits{E}} -\def\Hom{\operatorname{Hom}} % Homomorphism group -\def\id{\operatorname{id}} % identity -\def\im{\operatorname{im}} % image -\def\lcm{\operatorname{lcm}} -\def\lfs{\operatorname{lfs}} % local feature size -\def\poly{\operatorname{poly}} -\def\polylog{\operatorname{polylog}} -\def\rank{\operatorname{rank}} -\def\rel{\operatorname{rel\,}} % relative (interior, boundary, etc.) -\def\sgn{\operatorname{sgn}} -\def\vol{\operatorname{vol}} % volume - -\def\fp#1{^{\underline{#1}}} % falling powers: $n\fp{d}$ -\def\rp#1{^{\overline{#1}}} % rising powers: $n\rp{d}$ - -% --- Cheap displaystyle operators --- -\def\Frac#1#2{{\displaystyle\frac{#1}{#2}}} -\def\Sum{\sum\limits} -\def\Prod{\prod\limits} -\def\Union{\bigcup\limits} -\def\Inter{\bigcap\limits} -\def\Lor{\bigvee\limits} -\def\Land{\bigwedge\limits} -\def\Lim{\lim\limits} -\def\Max{\max\limits} -\def\Min{\min\limits} - -% ---- RELATORS ---- -\def\deq{\stackrel{\scriptscriptstyle\triangle}{=}} -\def\mapsfrom{\leftarrow\!\mapstochar\,} -\let\into\hookrightarrow % = one-to-one -\let\onto\twoheadrightarrow - -% ---- DELIMITER PAIRS ---- -\def\floor#1{\lfloor #1 \rfloor} -\def\ceil#1{\lceil #1 \rceil} -\def\seq#1{\langle #1 \rangle} -\def\set#1{\{ #1 \}} -\def\abs#1{\mathopen| #1 \mathclose|} % use instead of $|x|$ -\def\norm#1{\mathopen\| #1 \mathclose\|}% use instead of $\|x\|$ -\def\indic#1{\big[#1\big]} % indicator variable; Iverson notation - % e.g., Kronecker delta = [x=0] - -% --- Self-scaling delmiter pairs --- -\def\Floor#1{\left\lfloor #1 \right\rfloor} -\def\Ceil#1{\left\lceil #1 \right\rceil} -\def\Seq#1{\left\langle #1 \right\rangle} -\def\Set#1{\left\{ #1 \right\}} -\def\Abs#1{\left| #1 \right|} -\def\Norm#1{\left\| #1 \right\|} -\def\Paren#1{\left( #1 \right)} % need better macro name! -\def\Brack#1{\left[ #1 \right]} % need better macro name! -\def\Indic#1{\left[ #1 \right]} % indicator variable; Iverson notation - -% -% Macros to typeset sets like {foo|bar} with all three delimiters -% correctly scaled to fit. What I *really* want is a \middle macro -% that acts just like \left and \right. Grumble. -% -\def\Bigbar#1{\mathrel{\left|\vphantom{#1}\right.\n@space}} -\def\Setbar#1#2{\Set{#1 \Bigbar{#1 #2} #2}} -\def\Seqbar#1#2{\Seq{#1 \Bigbar{#1 #2} #2}} -\def\Brackbar#1#2{\Brack{#1 \Bigbar{#1 #2} #2}} - -% C-style arithmetic if-then-else -\def\arithif#1#2#3{#1 \mathbin? #2 \mathbin: #3} - -% Math mode fbox -\def\mfbox#1{\mathchoice{{\fbox{\ensuremath{\displaystyle #1}}}} - {{\fbox{\ensuremath{\textstyle #1}}}} - {{\fbox{\ensuremath{\scriptstyle #1}}}} - {{\fbox{\ensuremath{\scriptscriptstyle #1}}}}} - -% ---- ``ACCENTS'' ---- -% NB: Commands equivalent to \lrarrowfill and \overlrarrow are -% already defined in amstex! -\def\lrarrowfill{$\m@th\mathord\leftarrow\mkern-6mu% - \cleaders\hbox{$\mkern-2mu\mathord-\mkern-2mu$}\hfill - \mkern-6mu\mathord\rightarrow$} -\def\overlrarrow#1{\vbox{\ialign{##\crcr - \lrarrowfill\crcr\noalign{\kern-\p@\nointerlineskip} - $\hfil\displaystyle{#1}\hfil$\crcr}}} - -\def\Line#1{\!\overlrarrow{\vphantom{t}\smash{\,#1\,}}\!} -\def\Ray#1{\overrightarrow{\vphantom{t}#1\,}\!} -\def\Seg#1{\overline{\vphantom{t}#1}} - -% --- TEXT STYLES --- -\def\mathsc#1{\text{\textsc{#1}}} -\def\mathbs#1{\text{\boldmath\ensuremath{#1}}} - -% ---------------------------------------------------------------------- -% \begin{bigabstract}...\end{bigabstract} -% For use in documents with title pages. Use normal-sized text in -% the abstract! -% ---------------------------------------------------------------------- -\newenvironment{bigabstract}% -{\medskip\noindent\centerline{\textbf{\large\abstractname}}\begin{quotation}}% -{\end{quotation}} - -% ---------------------------------------------------------------------- -% Make captions smaller than the text, make their titles bold. -% Arguments: #1 == figure name: "Figure 5" -% #2 == caption: "Papers by \Erdos, 1900--2000 (projected)" -% Less space after floats and before caption, since captions are smaller -% ---------------------------------------------------------------------- -\@ifundefined{abovecaptionskip}{\newlength\abovecaptionskip} -\long\def\@makecaption#1#2{ - \vskip \abovecaptionskip - \setbox\@tempboxa\hbox{{\sf\footnotesize \textbf{#1.} #2}} - \ifdim \wd\@tempboxa >\hsize % IF longer than one line: - {\sf\footnotesize \textbf{#1.} #2\par}% THEN set as ordinary paragraph. - \else % ELSE center. - \hbox to\hsize{\hfil\box\@tempboxa\hfil} - \fi} -\dbltextfloatsep 18pt plus 2pt minus 4pt% was 20pt plus 2pt minus 4pt -\textfloatsep 18pt plus 2pt minus 4pt % was 20pt plus 2pt minus 4pt -\abovecaptionskip 6pt % was 10pt - -% ---------------------------------------------------------------------- -% Revised theorem environment: -% Add a period after the theorem number, and make theorems slanted -% instead of italic to help distinguish text from math. Use -% \boldmath in theorem label in case it includes math. -% ---------------------------------------------------------------------- -\def\@opargbegintheorem#1#2#3{\trivlist - \item[\hskip\labelsep{\bf\boldmath #1\ #2\ (#3).}]\sl} -\def\@begintheorem#1#2{\trivlist - \item[\hskip\labelsep{\bf\boldmath #1\ #2.}]\sl} - -% ---------------------------------------------------------------------- -% \newproof{type}{text}(style)[post]: -% Define a new type of unnumbered ``theorem'' environment. The last -% two arguments are optional; most environments will not use them. -% -% To change label style, put new style command in label: -% \newproof{comment}{\sf Comment} -% ---------------------------------------------------------------------- -\def\newproof#1#2{\@ifnextchar({\@snproof{#1}{#2}}{\@snproof{#1}{#2}(\rm)}} -\def\@snproof#1#2(#3){\@ifnextchar[{\@xnproof{#1}{#2}{#3}} - {\@xnproof{#1}{#2}{#3}[]}} - -\def\@xnproof#1#2#3[#4]{%\expandafter\@ifdefinable\csname #1\endcsname -{\global\@namedef{#1}{\@prf{#2}{#3}}\global\@namedef{end#1}{\@endprf{#4}}}} - -\def\@prf#1#2{\@ifnextchar[{\@xprf{#1}{#2}}{\@yprf{#1}{#2}}} -\def\@xprf#1#2[#3]{\@yprf{#1\ (#3)}{#2}} -\def\@yprf#1#2{\begin{trivlist}\item[\hskip\labelsep{\bf\boldmath #1:}]#2} - -\def\@endprf#1{#1\end{trivlist}} - -% -% Standard proof envrionment: last line has a halmos at the right margin. -% -\@ifundefined{square}{\let\square\Box}{} % grumble latex2e -\def\QED{\ensuremath{{\square}}} -\def\markatright#1{\leavevmode\unskip\nobreak\quad\hspace*{\fill}{#1}} -\def\qed{\markatright{\QED}} -\newproof{proof}{Proof}[\qed] -\newproof{sketch}{Proof Sketch}[\qed] - -\newenvironment{rawproof}% - {\begin{trivlist}\item[\hskip\labelsep\textbf{Proof:}]}% - {\qed\end{trivlist}} - -% -% If the proof ends with a displayed equation, use \aftermath just -% before \end{proof} to put the halmos in the ``right'' place. This -% may not work near page boundaries. -% -\def\aftermath{\par\vspace{-\belowdisplayskip}\vspace{-\parskip}\vspace{-\baselineskip}} - -% ---------------------------------------------------------------------- -% One-shot theoremish environment. For named things like ``Zorn's -% Lemma'' or ``The Death Leap Principle'' or ``The Zone Theorem''. -% To get one-shot proofish environment, put \rm inside. -% New improved version stolen from Erik Demaine. -% ---------------------------------------------------------------------- -\newenvironment{oneshot}[1]{\@begintheorem{#1}{\unskip}}{\@endtheorem} - -% ---------------------------------------------------------------------- -% Algorithm and code environments -- Algorithms are set in normal -% text, with 2em indenting, surrounded by a box. Code is set in -% typewriter text, with 4 space indenting, and no box. -% -% NOTE! The true width of the minipage environment is determined by -% the contents of the longest line, but ONLY because the minipage -% contains a tabbing environment, and nothing else. It's a HaX! -% -% Both environments need optional line numbering and comment macros, -% but bold keywords are just distracting. -% ---------------------------------------------------------------------- -\def\begin@lgo{\begin{minipage}{1in}\begin{tabbing} - \quad\=\qquad\=\qquad\=\qquad\=\qquad\=\qquad\=\qquad\=\kill} -\def\end@lgo{\end{tabbing}\end{minipage}} - -\newenvironment{algorithm} -{\begin{tabular}{|l|}\hline\begin@lgo} -{\end@lgo\\\hline\end{tabular}} - -\newenvironment{algo} -{\begin{center}\begin{algorithm}} -{\end{algorithm}\end{center}} - -\def\Comment#1{\textsf{\textsl{$\langle\!\langle$#1\/$\rangle\!\rangle$}}} - -\def\beginc@de{\noindent\begin{center}\begin{minipage}{1in}\tt - \begin{tabbing}~~~~\=~~~~\=~~~~\=~~~~\=~~~~\=~~~~\=~~~~\=\kill} -\def\endc@de{\end{tabbing}\end{minipage}\end{center}} - -\newenvironment{code}{\beginc@de}{\endc@de} - -% -% I think these only work with <1 line of text. Use sparingly!! -% -\def\textul#1{\underline{\smash{#1}\vphantom{,}}} -\def\strike#1{\ensuremath{\overline{\text{\smash{#1}\vphantom{.}}}}} - -% ---------------------------------------------------------------------- -% Include a file verbatim. Searches the TEXINPUTS path for the file, -% even though that's probably not what you really want. Stolen from -% ``verbatimfiles.sty'' by Chris Rowley and others. [Don't use their -% \vertbatimlisting macro; it has some bizarre side-effects!] -% ---------------------------------------------------------------------- -\def\verbinput#1{ -\begingroup\@verbatim\frenchspacing\@vobeyspaces\input#1\endgroup -} - -% ---------------------------------------------------------------------- -% \now -- Current time in h:mm AM/PM format -% \mdyy -- Today's date in m/d/yy format. Forget Y2K; this is for humans! -% ---------------------------------------------------------------------- -\newcount\timehh\timehh=\time -\divide\timehh by 60 -\newcount\timemm\timemm=\time -\count255=\timehh -\multiply\count255 by -60 -\advance\timemm by \count255 -\newif\iftimePM -\ifnum\timehh>11 \timePMtrue\else\timePMfalse\fi -\ifnum\timehh<1 \advance\timehh by 12\fi -\ifnum\timehh>12 \advance\timehh by -12\fi -\def\now{\number\timehh:\ifnum\timemm<10 0\fi\number\timemm - \iftimePM pm\else am\fi} -\newcount\mdYY\mdYY=\year -\count255=\year -\divide\count255 by 100 -\multiply\count255 by 100 -\advance\mdYY by -\count255 -\def\mdyy{\number\month/\number\day/\ifnum\mdYY<10 0\fi\number\mdYY} - -% ---------------------------------------------------------------------- -% Notes to myself -% ---------------------------------------------------------------------- -\def\n@te#1{\textsf{$\langle\!\langle$#1$\rangle\!\rangle$}\leavevmode} -\def\n@tew@rn{\GenericWarning{}{AUTHOR WARNING: Unresolved \protect\note}} - -\def\n@ten@te#1{\marginpar - [\hfill\llap{\textcircled{\small#1}$\!\Longrightarrow$}] - {\rlap{$\Longleftarrow\!$\textcircled{\small#1}}}} - -\def\n@tedingb@t{\@ifundefined{textmusicalnote} - {$\circledcirc$} % if you don't have textcomp - {\textmusicalnote}} % if you do have textcomp - -\def\note#1{\n@tew@rn\n@te{\n@ten@te{\n@tedingb@t}#1}} - -\def\sidenote#1{\marginpar{\tiny\sf #1}} - - -%---------------------------------------------------------------------- -% Bibliography aliases, so I can use mnemonic citation keys and -% geom.bib at the same time. \bibalias{foo}{bar} makes \cite{foo} -% act (almost) exactly like \cite{bar}. -%---------------------------------------------------------------------- -\def\bibalias#1#2{% - \global\@namedef{b@#1}{% - {\@ifundefined{b@#2}{\textsf{?}}{}\csname b@#2\endcsname}}} - -%---------------------------------------------------------------------- -% Flag bad citations and refernces in the margin. Dangerous if you -% have lots of undefined refs; use batchmode the first time. -% Incompatible with some document classes. -%---------------------------------------------------------------------- -\DeclareOption{flagerrors} -{ -\def\badcite{\ifinner\else\n@ten@te{\textcent}\fi} - -\def\badref{\ifinner\else\n@ten@te{$\Join$}\fi} - -\def\bibalias#1#2{% - \global\@namedef{b@#1}{% - {\@ifundefined{b@#2}{\textsf{>>#1??}}{}\csname b@#2\endcsname}}} - -\def\@citex[#1]#2{% - \let\@citea\@empty - \@cite{\@for\@citeb:=#2\do - {\@citea\def\@citea{,\penalty\@m\ }% - \edef\@citeb{\expandafter\@firstofone\@citeb\@empty}% - \if@filesw\immediate\write\@auxout{\string\citation{\@citeb}}\fi - \@ifundefined{b@\@citeb}{\mbox{\reset@font\sffamily>\@citeb?}% - \badcite% - \G@refundefinedtrue% - \@latex@warning - {Citation `\@citeb' on page \thepage \space undefined}}% - {\hbox{\csname b@\@citeb\endcsname}}}}{#1}} - -\def\@setref#1#2#3{ - \ifx#1\relax - \protect\G@refundefinedtrue - \badref\mbox{\reset@font\sffamily >#3?} - \@latex@warning{Reference `#3' on page \thepage \space undefined}% - \else - \expandafter#2#1\null - \fi} -} - - -% ---------------------------------------------------------------------- -% Draft notice. Put \DRAFT on the title page, in place of \date. -% ---------------------------------------------------------------------- -\def\draftnotice{Preliminary draft --- \mdyy\ --- Not for distribution} - -\def\DRAFT{ -\date{\fbox{\textsf{\textbf{\draftnotice}}}} -\def\@oddfoot{\footnotesize\hss\fbox{\textbf{\textsf{\draftnotice}}}\hss} -\let\@evenfoot\@oddfoot -} - -% ---------------------------------------------------------------------- -% Dingbats from the TeX/METAFONT-book manual font -% Use only with 11 or 12 pt text. -% Doesn't work with TeXtures, which doesn't know about manfnt. -% ---------------------------------------------------------------------- -\font\manual=manfnt -\def\goodcube{{\manual\char28}} % possible cube from MF-book -\def\badcube{{\manual\char29}} % impossible cube from MF-book -\def\starknot{{\manual\char30}} % 2,5 torus knot from MF-book -\def\target{{\manual\char36}} % concentric circles from MF-book -\def\xflower{{\manual\char38}} % X flower dingbat from MF-book -\def\tflower{{\manual\char39}} % + flower dingbat from MF-book -\def\changeto{{\manual\char121}}% change arrow -\def\dbend{{\manual\char127}} % dangerous bend sign - -% ---------------------------------------------------------------------- -% Dangerous bend environments, stolen from TeXbook and slightly -% massaged. -% -% Invoke as \begin{[d]danger}...\end{[d]danger}. The enclosed text -% is offset just like any other list (theorem, proof, etc.) Puts -% sign[s] in front of first two lines of first paragraph, which are -% (supposedly) never split by a page boundary. Does NOT shrink or -% otherwise modify the text. -% ---------------------------------------------------------------------- -% The dangerous bend signs are the correct size to match two lines of -% Computer Modern 9pt type. I really ought to scale them up to -% fit whatever size we're using, but I won't. Unfortunately, manfnt -% thinks it's a 10pt font, so if we want to match 11pt Computer -% Modern, we have to scale manfnt to 12.222222pt! Thanks, Don. -% -% TeX is a HaX. -% ---------------------------------------------------------------------- - -% Single danger -\def\danger{\begin{trivlist}\item[]\noindent% -\begingroup\hangindent=2.5pc\hangafter=-2\clubpenalty=10000% -\def\par{\endgraf\endgroup}% -\hbox to 0pt{\hskip-\hangindent\dbend\hfill}\ignorespaces} -\def\enddanger{\end{trivlist}} - -% Double danger -\def\ddanger{\begin{trivlist}\item[]\noindent% -\begingroup\hangindent=4pc\hangafter=-2\clubpenalty=10000% -\def\par{\endgraf\endgroup}% -\hbox to 0pt{\hskip-\hangindent\dbend\kern2pt\dbend\hfill}\ignorespaces} -\def\endddanger{\end{trivlist}} - -%---------------------------------------------------------------------- -% 'cramped' list style, stolen from Jeff Vitter -%---------------------------------------------------------------------- -\def\cramped - {\parskip\@outerparskip\@topsep\parskip - \@topsepadd2pt\itemsep0pt -% \settowidth{\labelwidth}{\@itemlabel} -% \advance\leftmargin-\labelsep -% \advance\leftmargin-\labelwidth -% \advance\@totalleftmargin-\leftmargin -% \advance\linewidth\leftmargin -% \parshape1\@totalleftmargin\linewidth -} - -%---------------------------------------------------------------------- -% More footnote symbols, please. -%---------------------------------------------------------------------- -\def\@fnsymbol#1{\ensuremath{\ifcase#1\or *\or \dagger\or \ddagger\or - \mathsection\or \mathparagraph\or \|\or **\or \dagger\dagger - \or \ddagger\ddagger \or \mathsection\mathsection \or - \mathparagraph\mathparagraph \else\@ctrerr\fi}} - -%---------------------------------------------------------------------- -% TeXbook style quotations -- I should really use the right font, tho. -%---------------------------------------------------------------------- -\newenvironment{rightquote}[1] -{\flushright\begin{minipage}{#1\textwidth} -\parskip0pt\footnotesize\sffamily\slshape} -{\end{minipage}\par\bigskip} -\def\quotee#1{\par\vspace{0.5ex}\flushright\unskip\textup{--- #1}} - -\ProcessOptions diff --git a/report/pyp_clustering/acl09-short/common-bak/prettyref.sty b/report/pyp_clustering/acl09-short/common-bak/prettyref.sty deleted file mode 100644 index 67940f3b..00000000 --- a/report/pyp_clustering/acl09-short/common-bak/prettyref.sty +++ /dev/null @@ -1,37 +0,0 @@ -%% -%% This is file `prettyref.sty', -%% generated with the docstrip utility. -%% -%% The original source files were: -%% -%% prettyref.dtx (with options: `style') -%% -%% Copyright (c) 1995 Kevin Ruland -%% -%% -%% prettyref v3.0 -%% -%% Copyright 1995,1998. by Kevin Ruland kevin@rodin.wustl.edu -%% -\ProvidesPackage{prettyref}[1998/07/09 v3.0] -\def\newrefformat#1#2{% - \@namedef{pr@#1}##1{#2}} -\newrefformat{eq}{\textup{(\ref{#1})}} -\newrefformat{lem}{Lemma \ref{#1}} -\newrefformat{thm}{Theorem \ref{#1}} -\newrefformat{cha}{Chapter \ref{#1}} -\newrefformat{sec}{Section \ref{#1}} -\newrefformat{tab}{Table \ref{#1} on page \pageref{#1}} -\newrefformat{fig}{Figure \ref{#1} on page \pageref{#1}} -\def\prettyref#1{\@prettyref#1:} -\def\@prettyref#1:#2:{% - \expandafter\ifx\csname pr@#1\endcsname\relax% - \PackageWarning{prettyref}{Reference format #1\space undefined}% - \ref{#1:#2}% - \else% - \csname pr@#1\endcsname{#1:#2}% - \fi% -} -\endinput -%% -%% End of file `prettyref.sty'. diff --git a/report/pyp_clustering/acl09-short/common-bak/scrunchacl.bst b/report/pyp_clustering/acl09-short/common-bak/scrunchacl.bst deleted file mode 100644 index 26e1fca6..00000000 --- a/report/pyp_clustering/acl09-short/common-bak/scrunchacl.bst +++ /dev/null @@ -1,1317 +0,0 @@ - -% BibTeX `scrunchacl' style file made by modifying `acl' style file. -% Lillian Lee, February 2003. Abbreviate first names, no explicit -% marker for page numbers, -% "editors" -> "eds", but still consistent with `fullname.sty'. No -% "and" between multiple authors. -% Also, might still have trouble with double-years, sometimes - -% BibTeX `acl' style file for BibTeX version 0.99c, LaTeX version 2.09 -% This version was made by modifying `aaai-named' format based on the master -% file by Oren Patashnik (PATASHNIK@SCORE.STANFORD.EDU) - -% Copyright (C) 1985, all rights reserved. -% Modifications Copyright 1988, Peter F. Patel-Schneider -% Further modifictions by Stuart Shieber, 1991, and Fernando Pereira, 1992. -% Copying of this file is authorized only if either -% (1) you make absolutely no changes to your copy, including name, or -% (2) if you do make changes, you name it something other than -% btxbst.doc, plain.bst, unsrt.bst, alpha.bst, and abbrv.bst. -% This restriction helps ensure that all standard styles are identical. - -% There are undoubtably bugs in this style. If you make bug fixes, -% improvements, etc. please let me know. My e-mail address is: -% pfps@spar.slb.com - -% Citation format: [author-last-name, year] -% [author-last-name and author-last-name, year] -% [author-last-name {\em et al.}, year] -% -% Reference list ordering: alphabetical by author or whatever passes -% for author in the absence of one. -% -% This BibTeX style has support for short (year only) citations. This -% is done by having the citations actually look like -% \citename{name-info, }year -% The LaTeX style has to have the following -% \let\@internalcite\cite -% \def\cite{\def\citename##1{##1}\@internalcite} -% \def\shortcite{\def\citename##1{}\@internalcite} -% \def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} -% which makes \shortcite the macro for short citations. - -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% -% Changes made by SMS for thesis style -% no emphasis on "et al." -% "Ph.D." includes periods (not "PhD") -% moved year to immediately after author's name -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% -ENTRY - { address - author - booktitle - chapter - edition - editor - howpublished - institution - journal - key - month - note - number - organization - pages - publisher - school - series - title - type - volume - year - } - {} - { label extra.label sort.label } - -INTEGERS { output.state before.all mid.sentence after.sentence after.block } - -FUNCTION {init.state.consts} -{ #0 'before.all := - #1 'mid.sentence := - #2 'after.sentence := - #3 'after.block := -} - -STRINGS { s t } - -FUNCTION {output.nonnull} -{ 's := - output.state mid.sentence = - { ", " * write$ } - { output.state after.block = - { add.period$ write$ - newline$ - "\newblock " write$ - } - { output.state before.all = - 'write$ - { add.period$ " " * write$ } - if$ - } - if$ - mid.sentence 'output.state := - } - if$ - s -} - -FUNCTION {output} -{ duplicate$ empty$ - 'pop$ - 'output.nonnull - if$ -} - -FUNCTION {output.check} -{ 't := - duplicate$ empty$ - { pop$ "empty " t * " in " * cite$ * warning$ } - 'output.nonnull - if$ -} - - -FUNCTION {output.bibitem} -{ - "\bibitem[" write$ - label write$ - "]{" write$ - - cite$ write$ - "}" write$ - "" - before.all 'output.state := -} - -FUNCTION {fin.entry} -{ add.period$ - write$ - "\bibsnip" write$ - newline$ -} - -FUNCTION {new.block} -{ output.state before.all = - 'skip$ - { after.block 'output.state := } - if$ -} - -FUNCTION {new.sentence} -{ output.state after.block = - 'skip$ - { output.state before.all = - 'skip$ - { after.sentence 'output.state := } - if$ - } - if$ -} - -FUNCTION {not} -{ { #0 } - { #1 } - if$ -} - -FUNCTION {and} -{ 'skip$ - { pop$ #0 } - if$ -} - -FUNCTION {or} -{ { pop$ #1 } - 'skip$ - if$ -} - -FUNCTION {new.block.checka} -{ empty$ - 'skip$ - 'new.block - if$ -} - -FUNCTION {new.block.checkb} -{ empty$ - swap$ empty$ - and - 'skip$ - 'new.block - if$ -} - -FUNCTION {new.sentence.checka} -{ empty$ - 'skip$ - 'new.sentence - if$ -} - -FUNCTION {new.sentence.checkb} -{ empty$ - swap$ empty$ - and - 'skip$ - 'new.sentence - if$ -} - -FUNCTION {field.or.null} -{ duplicate$ empty$ - { pop$ "" } - 'skip$ - if$ -} - -FUNCTION {emphasize} -{ duplicate$ empty$ - { pop$ "" } - { "{\em " swap$ * "}" * } - if$ -} - -INTEGERS { nameptr namesleft numnames } - - - -FUNCTION {format.names} -{ 's := - #1 'nameptr := - s num.names$ 'numnames := - numnames 'namesleft := - { namesleft #0 > } - { s nameptr "{f.~}{vv~}{ll}{, jj}" format.name$ 't := - nameptr #1 > - { namesleft #1 > - { ", " * t * } - { numnames #2 > - { "" * } - 'skip$ - if$ - t "others" = - { " et~al." * } - { ", " * t * } - if$ - } - if$ - } - 't - if$ - nameptr #1 + 'nameptr := - namesleft #1 - 'namesleft := - } - while$ -} - -FUNCTION {format.authors} -{ author empty$ - { "" } - { author format.names } - if$ -} - -FUNCTION {format.editors} -{ editor empty$ - { "" } - { editor format.names - editor num.names$ #1 > - { ", eds." * } - { ", ed." * } - if$ - } - if$ -} - -FUNCTION {format.title} -{ title empty$ - { "" } - { title "t" change.case$ } - if$ -} - -FUNCTION {n.dashify} -{ 't := - "" - { t empty$ not } - { t #1 #1 substring$ "-" = - { t #1 #2 substring$ "--" = not - { "--" * - t #2 global.max$ substring$ 't := - } - { { t #1 #1 substring$ "-" = } - { "-" * - t #2 global.max$ substring$ 't := - } - while$ - } - if$ - } - { t #1 #1 substring$ * - t #2 global.max$ substring$ 't := - } - if$ - } - while$ -} - -FUNCTION {format.date} -{ year empty$ - { month empty$ - { "" } - { "there's a month but no year in " cite$ * warning$ - month - } - if$ - } - { month empty$ - 'year - { month " " * year * } - if$ - } - if$ -} - -FUNCTION {format.btitle} -{ title emphasize -} - -FUNCTION {tie.or.space.connect} -{ duplicate$ text.length$ #3 < - { "~" } - { " " } - if$ - swap$ * * -} - -FUNCTION {either.or.check} -{ empty$ - 'pop$ - { "can't use both " swap$ * " fields in " * cite$ * warning$ } - if$ -} - -FUNCTION {format.bvolume} -{ volume empty$ - { "" } - { "volume" volume tie.or.space.connect - series empty$ - 'skip$ - { " of " * series emphasize * } - if$ - "volume and number" number either.or.check - } - if$ -} - -FUNCTION {format.number.series} -{ volume empty$ - { number empty$ - { series field.or.null } - { output.state mid.sentence = - { "number" } - { "Number" } - if$ - number tie.or.space.connect - series empty$ - { "there's a number but no series in " cite$ * warning$ } - { " in " * series * } - if$ - } - if$ - } - { "" } - if$ -} - -FUNCTION {format.edition} -{ edition empty$ - { "" } - { output.state mid.sentence = - { edition "l" change.case$ " edition" * } - { edition "t" change.case$ " edition" * } - if$ - } - if$ -} - -INTEGERS { multiresult } - -FUNCTION {multi.page.check} -{ 't := - #0 'multiresult := - { multiresult not - t empty$ not - and - } - { t #1 #1 substring$ - duplicate$ "-" = - swap$ duplicate$ "," = - swap$ "+" = - or or - { #1 'multiresult := } - { t #2 global.max$ substring$ 't := } - if$ - } - while$ - multiresult -} - -FUNCTION {format.pages} -{ pages empty$ - { "" } - { pages multi.page.check - { "" pages n.dashify tie.or.space.connect } - { "pg." pages tie.or.space.connect } - if$ - } - if$ -} - -FUNCTION {format.year.label} -{ year extra.label * -} - -FUNCTION {format.vol.num.pages} -{ volume field.or.null - number empty$ - 'skip$ - { "(" number * ")" * * - volume empty$ - { "there's a number but no volume in " cite$ * warning$ } - 'skip$ - if$ - } - if$ - pages empty$ - 'skip$ - { duplicate$ empty$ - { pop$ format.pages } - { ":" * pages n.dashify * } - if$ - } - if$ -} - -FUNCTION {format.chapter.pages} -{ chapter empty$ - 'format.pages - { type empty$ - { "chapter" } - { type "l" change.case$ } - if$ - chapter tie.or.space.connect - pages empty$ - 'skip$ - { ", " * format.pages * } - if$ - } - if$ -} - -FUNCTION {format.in.ed.booktitle} -{ booktitle empty$ - { "" } - { editor empty$ - { "In " booktitle emphasize * } - { "In " format.editors * ", " * booktitle emphasize * } - if$ - } - if$ -} - -FUNCTION {empty.misc.check} -{ author empty$ title empty$ howpublished empty$ - month empty$ year empty$ note empty$ - and and and and and - - key empty$ not and - - { "all relevant fields are empty in " cite$ * warning$ } - 'skip$ - if$ -} - -FUNCTION {format.thesis.type} -{ type empty$ - 'skip$ - { pop$ - type "t" change.case$ - } - if$ -} - -FUNCTION {format.tr.number} -{ type empty$ - { "Technical Report" } - 'type - if$ - number empty$ - { "t" change.case$ } - { number tie.or.space.connect } - if$ -} - -FUNCTION {format.article.crossref} -{ key empty$ - { journal empty$ - { "need key or journal for " cite$ * " to crossref " * crossref * - warning$ - "" - } - { "In {\em " journal * "\/}" * } - if$ - } - { "In " key * } - if$ - " \cite{" * crossref * "}" * -} - -FUNCTION {format.crossref.editor} -{ editor #1 "{vv~}{ll}" format.name$ - editor num.names$ duplicate$ - #2 > - { pop$ " et~al." * } - { #2 < - 'skip$ - { editor #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" = - { " et~al." * } - { " and " * editor #2 "{vv~}{ll}" format.name$ * } - if$ - } - if$ - } - if$ -} - -FUNCTION {format.book.crossref} -{ volume empty$ - { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ - "In " - } - { "Volume" volume tie.or.space.connect - " of " * - } - if$ - editor empty$ - editor field.or.null author field.or.null = - or - { key empty$ - { series empty$ - { "need editor, key, or series for " cite$ * " to crossref " * - crossref * warning$ - "" * - } - { "{\em " * series * "\/}" * } - if$ - } - { key * } - if$ - } - { format.crossref.editor * } - if$ - " \cite{" * crossref * "}" * -} - -FUNCTION {format.incoll.inproc.crossref} -{ editor empty$ - editor field.or.null author field.or.null = - or - { key empty$ - { booktitle empty$ - { "need editor, key, or booktitle for " cite$ * " to crossref " * - crossref * warning$ - "" - } - { "In {\em " booktitle * "\/}" * } - if$ - } - { "In " key * } - if$ - } - { "In " format.crossref.editor * } - if$ - " \cite{" * crossref * "}" * -} - -FUNCTION {article} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - crossref missing$ - { journal emphasize "journal" output.check - format.vol.num.pages output - } - { format.article.crossref output.nonnull - format.pages output - } - if$ - new.block - note output - fin.entry -} - -FUNCTION {book} -{ output.bibitem - author empty$ - { format.editors "author and editor" output.check } - { format.authors output.nonnull - crossref missing$ - { "author and editor" editor either.or.check } - 'skip$ - if$ - } - if$ - new.block - format.year.label "year" output.check - new.block - format.btitle "title" output.check - crossref missing$ - { format.bvolume output - new.block - format.number.series output - new.sentence - publisher "publisher" output.check - address output - } - { new.block - format.book.crossref output.nonnull - } - if$ - format.edition output - note output - fin.entry -} - -FUNCTION {booklet} -{ output.bibitem - format.authors output - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - howpublished address new.block.checkb - howpublished output - address output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {inbook} -{ output.bibitem - author empty$ - { format.editors "author and editor" output.check } - { format.authors output.nonnull - crossref missing$ - { "author and editor" editor either.or.check } - 'skip$ - if$ - } - if$ - format.year.label "year" output.check - new.block - new.block - format.btitle "title" output.check - crossref missing$ - { format.bvolume output - format.chapter.pages "chapter and pages" output.check - new.block - format.number.series output - new.sentence - publisher "publisher" output.check - address output - } - { format.chapter.pages "chapter and pages" output.check - new.block - format.book.crossref output.nonnull - } - if$ - format.edition output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {incollection} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - crossref missing$ - { format.in.ed.booktitle "booktitle" output.check - format.bvolume output - format.number.series output - format.chapter.pages output - new.sentence - publisher "publisher" output.check - address output - format.edition output - } - { format.incoll.inproc.crossref output.nonnull - format.chapter.pages output - } - if$ - new.block - note output - fin.entry -} - -FUNCTION {inproceedings} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - crossref missing$ - { format.in.ed.booktitle "booktitle" output.check - format.bvolume output - format.number.series output - format.pages output - address empty$ - { organization publisher new.sentence.checkb - organization output - publisher output - } - { address output.nonnull - new.sentence - organization output - publisher output - } - if$ - } - { format.incoll.inproc.crossref output.nonnull - format.pages output - } - if$ - new.block - note output - fin.entry -} - -FUNCTION {conference} { inproceedings } - -FUNCTION {manual} -{ output.bibitem - author empty$ - { organization empty$ - 'skip$ - { organization output.nonnull - address output - } - if$ - } - { format.authors output.nonnull } - if$ - format.year.label "year" output.check - new.block - new.block - format.btitle "title" output.check - author empty$ - { organization empty$ - { address new.block.checka - address output - } - 'skip$ - if$ - } - { organization address new.block.checkb - organization output - address output - } - if$ - format.edition output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {mastersthesis} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - "Master's thesis" format.thesis.type output.nonnull - school "school" output.check - address output - note output - fin.entry -} - -FUNCTION {misc} -{ output.bibitem - format.authors output - new.block - format.year.label output - new.block - title howpublished new.block.checkb - format.title output - howpublished new.block.checka - howpublished output - format.date output - new.block - note output - fin.entry - empty.misc.check -} - -FUNCTION {phdthesis} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.btitle "title" output.check - new.block - "{Ph.D.} thesis" format.thesis.type output.nonnull - school "school" output.check - address output - note output - fin.entry -} - -FUNCTION {proceedings} -{ output.bibitem - editor empty$ - { organization output } - { format.editors output.nonnull } - if$ - new.block - format.year.label "year" output.check - new.block - format.btitle "title" output.check - format.bvolume output - format.number.series output - address empty$ - { editor empty$ - { publisher new.sentence.checka } - { organization publisher new.sentence.checkb - organization output - } - if$ - publisher output - format.date output - } - { address output.nonnull - format.date output - new.sentence - editor empty$ - 'skip$ - { organization output } - if$ - publisher output - } - if$ - new.block - note output - fin.entry -} - -FUNCTION {techreport} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - format.tr.number output.nonnull - institution "institution" output.check - address output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {unpublished} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - note "note" output.check - fin.entry -} - -FUNCTION {default.type} { misc } - -MACRO {jan} {"January"} - -MACRO {feb} {"February"} - -MACRO {mar} {"March"} - -MACRO {apr} {"April"} - -MACRO {may} {"May"} - -MACRO {jun} {"June"} - -MACRO {jul} {"July"} - -MACRO {aug} {"August"} - -MACRO {sep} {"September"} - -MACRO {oct} {"October"} - -MACRO {nov} {"November"} - -MACRO {dec} {"December"} - -MACRO {acmcs} {"ACM Computing Surveys"} - -MACRO {acta} {"Acta Informatica"} - -MACRO {cacm} {"Communications of the ACM"} - -MACRO {ibmjrd} {"IBM Journal of Research and Development"} - -MACRO {ibmsj} {"IBM Systems Journal"} - -MACRO {ieeese} {"IEEE Transactions on Software Engineering"} - -MACRO {ieeetc} {"IEEE Transactions on Computers"} - -MACRO {ieeetcad} - {"IEEE Transactions on Computer-Aided Design of Integrated Circuits"} - -MACRO {ipl} {"Information Processing Letters"} - -MACRO {jacm} {"Journal of the ACM"} - -MACRO {jcss} {"Journal of Computer and System Sciences"} - -MACRO {scp} {"Science of Computer Programming"} - -MACRO {sicomp} {"SIAM Journal on Computing"} - -MACRO {tocs} {"ACM Transactions on Computer Systems"} - -MACRO {tods} {"ACM Transactions on Database Systems"} - -MACRO {tog} {"ACM Transactions on Graphics"} - -MACRO {toms} {"ACM Transactions on Mathematical Software"} - -MACRO {toois} {"ACM Transactions on Office Information Systems"} - -MACRO {toplas} {"ACM Transactions on Programming Languages and Systems"} - -MACRO {tcs} {"Theoretical Computer Science"} - -READ - -FUNCTION {sortify} -{ purify$ - "l" change.case$ -} - -INTEGERS { len } - -FUNCTION {chop.word} -{ 's := - 'len := - s #1 len substring$ = - { s len #1 + global.max$ substring$ } - 's - if$ -} - -INTEGERS { et.al.char.used } - -FUNCTION {initialize.et.al.char.used} -{ #0 'et.al.char.used := -} - -EXECUTE {initialize.et.al.char.used} - -FUNCTION {format.lab.names} -{ 's := - s num.names$ 'numnames := - - numnames #1 = - { s #1 "{vv }{ll}" format.name$ } - { numnames #2 = - { s #1 "{vv }{ll }and " format.name$ s #2 "{vv }{ll}" format.name$ * - } - { s #1 "{vv }{ll }\bgroup et al.\egroup " format.name$ } - if$ - } - if$ - -} - -FUNCTION {author.key.label} -{ author empty$ - { key empty$ - - { cite$ #1 #3 substring$ } - - { key #3 text.prefix$ } - if$ - } - { author format.lab.names } - if$ -} - -FUNCTION {author.editor.key.label} -{ author empty$ - { editor empty$ - { key empty$ - - { cite$ #1 #3 substring$ } - - { key #3 text.prefix$ } - if$ - } - { editor format.lab.names } - if$ - } - { author format.lab.names } - if$ -} - -FUNCTION {author.key.organization.label} -{ author empty$ - { key empty$ - { organization empty$ - - { cite$ #1 #3 substring$ } - - { "The " #4 organization chop.word #3 text.prefix$ } - if$ - } - { key #3 text.prefix$ } - if$ - } - { author format.lab.names } - if$ -} - -FUNCTION {editor.key.organization.label} -{ editor empty$ - { key empty$ - { organization empty$ - - { cite$ #1 #3 substring$ } - - { "The " #4 organization chop.word #3 text.prefix$ } - if$ - } - { key #3 text.prefix$ } - if$ - } - { editor format.lab.names } - if$ -} - -FUNCTION {calc.label} -{ type$ "book" = - type$ "inbook" = - or - 'author.editor.key.label - { type$ "proceedings" = - 'editor.key.organization.label - { type$ "manual" = - 'author.key.organization.label - 'author.key.label - if$ - } - if$ - } - if$ - duplicate$ - - "\protect\citename{" swap$ * "}" * - year field.or.null purify$ * - 'label := - year field.or.null purify$ * - - sortify 'sort.label := -} - -FUNCTION {sort.format.names} -{ 's := - #1 'nameptr := - "" - s num.names$ 'numnames := - numnames 'namesleft := - { namesleft #0 > } - { nameptr #1 > - { " " * } - 'skip$ - if$ - - s nameptr "{vv{ } }{ll{ }}{ ff{ }}{ jj{ }}" format.name$ 't := - - nameptr numnames = t "others" = and - { "et al" * } - { t sortify * } - if$ - nameptr #1 + 'nameptr := - namesleft #1 - 'namesleft := - } - while$ -} - -FUNCTION {sort.format.title} -{ 't := - "A " #2 - "An " #3 - "The " #4 t chop.word - chop.word - chop.word - sortify - #1 global.max$ substring$ -} - -FUNCTION {author.sort} -{ author empty$ - { key empty$ - { "to sort, need author or key in " cite$ * warning$ - "" - } - { key sortify } - if$ - } - { author sort.format.names } - if$ -} - -FUNCTION {author.editor.sort} -{ author empty$ - { editor empty$ - { key empty$ - { "to sort, need author, editor, or key in " cite$ * warning$ - "" - } - { key sortify } - if$ - } - { editor sort.format.names } - if$ - } - { author sort.format.names } - if$ -} - -FUNCTION {author.organization.sort} -{ author empty$ - { organization empty$ - { key empty$ - { "to sort, need author, organization, or key in " cite$ * warning$ - "" - } - { key sortify } - if$ - } - { "The " #4 organization chop.word sortify } - if$ - } - { author sort.format.names } - if$ -} - -FUNCTION {editor.organization.sort} -{ editor empty$ - { organization empty$ - { key empty$ - { "to sort, need editor, organization, or key in " cite$ * warning$ - "" - } - { key sortify } - if$ - } - { "The " #4 organization chop.word sortify } - if$ - } - { editor sort.format.names } - if$ -} - -FUNCTION {presort} - -{ calc.label - sort.label - " " - * - type$ "book" = - - type$ "inbook" = - or - 'author.editor.sort - { type$ "proceedings" = - 'editor.organization.sort - { type$ "manual" = - 'author.organization.sort - 'author.sort - if$ - } - if$ - } - if$ - - * - - " " - * - year field.or.null sortify - * - " " - * - title field.or.null - sort.format.title - * - #1 entry.max$ substring$ - 'sort.key$ := -} - -ITERATE {presort} - -SORT - -STRINGS { longest.label last.sort.label next.extra } - -INTEGERS { longest.label.width last.extra.num } - -FUNCTION {initialize.longest.label} -{ "" 'longest.label := - #0 int.to.chr$ 'last.sort.label := - "" 'next.extra := - #0 'longest.label.width := - #0 'last.extra.num := -} - -FUNCTION {forward.pass} -{ last.sort.label sort.label = - { last.extra.num #1 + 'last.extra.num := - last.extra.num int.to.chr$ 'extra.label := - } - { "a" chr.to.int$ 'last.extra.num := - "" 'extra.label := - sort.label 'last.sort.label := - } - if$ -} - -FUNCTION {reverse.pass} -{ next.extra "b" = - { "a" 'extra.label := } - 'skip$ - if$ - label extra.label * 'label := - label width$ longest.label.width > - { label 'longest.label := - label width$ 'longest.label.width := - } - 'skip$ - if$ - extra.label 'next.extra := -} - -EXECUTE {initialize.longest.label} - -ITERATE {forward.pass} - -REVERSE {reverse.pass} - -FUNCTION {begin.bib} - -{ et.al.char.used - { "\newcommand{\etalchar}[1]{$^{#1}$}" write$ newline$ } - 'skip$ - if$ - preamble$ empty$ - - 'skip$ - { preamble$ write$ newline$ } - if$ - - "\begin{thebibliography}{" "}" * write$ newline$ - -} - -EXECUTE {begin.bib} - -EXECUTE {init.state.consts} - -ITERATE {call.type$} - -FUNCTION {end.bib} -{ newline$ - "\end{thebibliography}" write$ newline$ -} - -EXECUTE {end.bib} - - diff --git a/report/pyp_clustering/acl09-short/common-bak/standard.bib b/report/pyp_clustering/acl09-short/common-bak/standard.bib deleted file mode 100644 index be782326..00000000 --- a/report/pyp_clustering/acl09-short/common-bak/standard.bib +++ /dev/null @@ -1,2702 +0,0 @@ -%% This BibTeX bibliography file was created using BibDesk. -%% http://bibdesk.sourceforge.net/ - - -%% Created for Phil Blunsom at 2009-10-22 14:37:31 +0100 - - -%% Saved with string encoding Unicode (UTF-8) - - -@string{+aaai1980 = {Proc.\ of the 1st Conference on Artificial Intelligence (AAAI-80)}} - -@string{+aaai1991 = {Proc.\ of the 9th Annual Conference on Artificial Intelligence (AAAI-91)}} - -@string{+acl1983 = {Proc.\ of the 21st Annual Meeting of the ACL}} - -@string{+acl1984 = {Proc.\ of the 22nd Annual Meeting of the ACL}} - -@string{+acl1985 = {Proc.\ of the 23rd Annual Meeting of the ACL}} - -@string{+acl1986 = {Proc.\ of the 24th Annual Meeting of the ACL}} - -@string{+acl1987 = {Proc.\ of the 25th Annual Meeting of the ACL}} - -@string{+acl1988 = {Proc.\ of the 26th Annual Meeting of the ACL}} - -@string{+acl1989 = {Proc.\ of the 27th Annual Meeting of the ACL}} - -@string{+acl1990 = {Proc.\ of the 28th Annual Meeting of the ACL}} - -@string{+acl1991 = {Proc.\ of the 29th Annual Meeting of the ACL}} - -@string{+acl1992 = {Proc.\ of the 30th Annual Meeting of the ACL}} - -@string{+acl1992-ss = {Proc.\ of the 30th Annual Meeting of the ACL, Student Session}} - -@string{+acl1993 = {Proc.\ of the 31st Annual Meeting of the ACL}} - -@string{+acl1994 = {Proc.\ of the 32nd Annual Meeting of the ACL}} - -@string{+acl1995 = {Proc.\ of the 33rd Annual Meeting of the ACL}} - -@string{+acl1996 = {Proc.\ of the 34th Annual Meeting of the ACL}} - -@string{+acl1997 = {Proc.\ of the 35th Annual Meeting of the ACL and 8th Conference of the EACL (ACL-EACL'97)}} - -@string{+acl1997ws-ca = {Proc.\ of ACL/EACL'97 Workshop on Natural Language Processing for Communication Aids}} - -@string{+acl1997ws-ie = {Proc.\ of ACL/EACL'97 Workshop on Automatic Information Extraction and Building of Lexical Semantic Resources for NLP Applications}} - -@string{+acl1998 = {Proc.\ of the 36th Annual Meeting of the ACL and 17th International Conference on Computational Linguistics: COLING/ACL-98}} - -@string{+acl1998-ss = {Proc.\ of the 36th Annual Meeting of the ACL and 17th International Conference on Computational Linguistics (COLING/ACL-98), Student Session}} - -@string{+acl1999 = {Proc.\ of the 37th Annual Meeting of the ACL}} - -@string{+acl2000 = {Proc.\ of the 38th Annual Meeting of the ACL}} - -@string{+acl2001 = {Proc.\ of the 39th Annual Meeting of the ACL and 10th Conference of the EACL (ACL-EACL 2001)}} - -@string{+acl2001-ddmt = {Proc.\ of the ACL/EACL 2001 Workshop on Data-Driven Methods in Machine Translation}} - -@string{+acl2001-wscoll = {Proc.\ of the ACL/EACL 2001 Workshop on the Computational Extraction, Analysis and Exploitation of Collocations}} - -@string{+acl2002 = {Proc.\ of the 40th Annual Meeting of the ACL and 3rd Annual Meeting of the NAACL (ACL-2002)}} - -@string{+acl2002-lexacq = {Proc.\ of the ACL-2002 SIGLEX Workshop on Unsupervised Lexical Acquisition}} - -@string{+acl2002-sigphon = {Proc.\ of the 6th Meeting of the ACL Special Interest Group in Computational Phonology}} - -@string{+acl2002-ss = {Proc.\ of the Student Research Workshop, 40th Annual Meeting of the ACL (ACL-2002)}} - -@string{+acl2002-wsd = {Proc.\ of the ACL-2002 Workshop on Word Sense Disambiguation: Recent Successes and Future Directions}} - -@string{+acl2003 = {Proc.\ of the 41st Annual Meeting of the ACL (ACL-2003)}} - -@string{+acl2003-mwe = {Proc.\ of the ACL-2003 Workshop on Multiword Expressions: Analysis, Acquisition and Treatment}} - -@string{+acl2004 = {Proc.\ of the 42nd Annual Meeting of the ACL (ACL-2004)}} - -@string{+acl2004-mwe = {Proc.\ of the ACL 2004 Workshop on Multiword Expressions: Integrating Processing}} - -@string{+acl2004-senseval = {Proc.\ of Senseval-3: Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text}} - -@string{+acl2004-tmi = {Proc.\ of the 2nd Workshop on Text Meaning and Interpretation}} - -@string{+acl2005 = {Proc.\ of the 43rd Annual Meeting of the ACL (ACL-2005)}} - -@string{+acl2005-dla = {Proc.\ of the ACL 2005 Workshop on Deep Lexical Acquisition}} - -@string{+acl2005-pt = {Proc.\ of the ACL 2005 Workshop on Parallel Texts}} - -@string{+acl2006 = {Proc.\ of the 44th Annual Meeting of the ACL and 21st International Conference on Computational Linguistics (COLING/ACL-2006)}} - -@string{+acl2007 = {Proc.\ of the 45th Annual Meeting of the ACL (ACL-2007)}} - -@string{+acl2008 = {Proc.\ of the 46th Annual Conference of the Association for Computational Linguistics: Human Language Technologies (ACL-08:HLT)}} - 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-@string{+emnlp2003 = {Proc.\ of the 2003 Conference on Empirical Methods in Natural Language Processing (EMNLP-2003)}} - -@string{+emnlp2004 = {Proc.\ of the 2004 Conference on Empirical Methods in Natural Language Processing (EMNLP-2004)}} - -@string{+emnlp2005 = {Proc.\ of the 2005 Conference on Empirical Methods in Natural Language Processing (EMNLP-2005)}} - -@string{+emnlp2006 = {Proc.\ of the 2006 Conference on Empirical Methods in Natural Language Processing (EMNLP-2006)}} - -@string{+emnlp2007 = {Proc.\ of the 2007 Conference on Empirical Methods in Natural Language Processing (EMNLP-2007)}} - -@string{+ewnlg1999 = {Proc.\ of the 7th European Workshop on Natural Language Generation (EWNLG'99)}} - -@string{+gl2002 = {Proc.\ of the 1st International Workshop on Generative Approaches to the Lexicon}} - -@string{+gl2003 = {Proc.\ of the 2nd International Workshop on Generative Approaches to the Lexicon}} - -@string{+hlt2001 = {Proc.\ of Human Language Technology (HLT) 2001}} - -@string{+hpsg2002 = {Proc.\ of the 9th International Conference on Head-Driven Phrase Structure Grammar (HPSG-2002)}} - 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-@string{+ijcai1993 = {Proc.\ of the 13th International Joint Conference on Artificial Intelligence (IJCAI-93)}} - -@string{+ijcai1995 = {Proc.\ of the 14th International Joint Conference on Artificial Intelligence (IJCAI-95)}} - -@string{+ijcai1997 = {Proc.\ of the 15th International Joint Conference on Artificial Intelligence (IJCAI-97)}} - -@string{+ijcai1999 = {Proc.\ of the 16th International Joint Conference on Artificial Intelligence (IJCAI-99)}} - -@string{+ijcnlp2004 = {Proc.\ of the First International Joint Conference on Natural Language Processing (IJCNLP-2004)}} - -@string{+iral2003 = {Proc.\ of the The Sixth International Workshop on Information Retrieval with Asian Languages (IRAL2003)}} - -@string{+iwslt2005 = {Proc.\ of the International Workshop on Spoken Language Translation}} - -@string{+jml = {Journal of Memory and Language}} - -@string{+jnlp = {Journal of Natural Language Processing}} - -@string{+jnlp1996 = {Proc.\ of the 2nd Annual Meeting of the Association for Natural Language Processing (Japan)}} - -@string{+jnlp1998 = {Proc.\ of the 4th Annual Meeting of the Association for Natural Language Processing (Japan)}} - -@string{+jnlp1999 = {Proc.\ of the 5th Annual Meeting of the Association for Natural Language Processing (Japan)}} - -@string{+jnlp2001 = {Proc.\ of the 7th Annual Meeting of the Association for Natural Language Processing (Japan)}} - -@string{+jnlp2002 = {Proc.\ of the 8th Annual Meeting of the Association for Natural Language Processing (Japan)}} - -@string{+jnlp2004 = {Proc.\ of the 10th Annual Meeting of the Association for Natural Language Processing (Japan)}} - -@string{+lrec1998 = {Proc.\ of the 1st International Conference on Language Resources and Evaluation (LREC-98)}} - -@string{+lrec2000 = {Proc.\ of the 2nd International Conference on Language Resources and Evaluation (LREC-2000)}} - -@string{+lrec2002 = {Proc.\ of the 3rd International Conference on Language Resources and Evaluation (LREC-2002)}} - -@string{+lrec2004 = {Proc.\ of the 4th International Conference on Language Resources and Evaluation (LREC-2004)}} - -@string{+lrec2006 = {Proc.\ of the 5th International Conference on Language Resources and Evaluation (LREC-2006)}} - -@string{+lsa = {Proc.\ of the Linguistics Society of America (LSA) Annual Meeting}} - -@string{+ml = {Machine Learning}} - -@string{+mtsummit1997 = {Proc.\ of the Fifth Machine Translation Summit (MT Summit V)}} - -@string{+mtsummit2003 = {Proc.\ of the Ninth Machine Translation Summit (MT Summit IX)}} - -@string{+naacl2000 = {Proc.\ of the 1st Annual Meeting of the North American Chapter of Association for Computational Linguistics (NAACL2000)}} - -@string{+naacl2001 = {Proc.\ of the 2nd Annual Meeting of the North American Chapter of Association for Computational Linguistics (NAACL2001)}} - -@string{+naacl2001-wn = {Proc.\ of the NAACL 2001 Workshop on WordNet and Other Lexical Resources: Applications, Extensions and Customizations}} - -@string{+naacl2002 = {Proc.\ of the 40th Annual Meeting of the ACL and 3rd Annual Meeting of the NAACL (ACL-2002)}} - -@string{+naacl2003 = {Proc.\ of the 3rd International Conference on Human Language Technology Research and 4th Annual Meeting of the NAACL (HLT-NAACL 2003)}} - -@string{+naacl2004 = {Proc.\ of the 4th International Conference on Human Language Technology Research and 5th Annual Meeting of the NAACL (HLT-NAACL 2004)}} - -@string{+naacl2005 = {Proc.\ of the 5th International Conference on Human Language Technology Research and 6th Annual Meeting of the NAACL (HLT-NAACL 2005)}} - -@string{+naacl2006 = {Proc.\ of the 6th International Conference on Human Language Technology Research and 7th Annual Meeting of the NAACL (HLT-NAACL 2006)}} - -@string{+naacl2006-smt = {Proc.\ of the HLT-NAACL 2006 Workshop on Statistical Machine Translation}} - -@string{+naacl2007 = {Proc.\ of the 7th International Conference on Human Language Technology Research and 8th Annual Meeting of the NAACL (HLT-NAACL 2007)}} - -@string{+naacl2007-ssst = {Proc.\ of the HLT-NAACL Workshop on Syntax and Structure in Statistical Translation (SSST 2007)}} - -@string{+nemlap1994 = {Proc.\ of the Conference on New Methods in Natural Language Processing}} - -@string{+nemlap1996 = {Proc.\ of the 2nd International Conference on New Methods in Natural Language Processing}} - -@string{+nemlap1998 = {Proc.\ of the Joint Conference on New Methods in Natural Language Processing and Natural Language Learning (NeMLaP3/CoNLL-98)}} - -@string{+nle = {Natural Language Engineering}} - -@string{+nlprs1995 = {Proc.\ of the 3rd Natural Language Processing Pacific Rim Symposium 1995 (NLPRS'95)}} - -@string{+nlprs1997 = {Proc.\ of the 4th Natural Language Processing Pacific Rim Symposium 1997 (NLPRS'97)}} - -@string{+paclic2000 = {Proc.\ of the 14th Pacific Asia Conference on Language, Information and Computation (PACLIC 14)}} - -@string{+paclic2004 = {Proc.\ of the 18th Pacific Asia Conference on Language, Information and Computation (PACLIC 18)}} - -@string{+pacling2005 = {Proc.\ of the 6th Meeting of the Pacific Association for Computational Linguistics (PACLING-2005)}} - -@string{+papillon2003 = {Proc.\ of the Papillon-2003 Workshop}} - -@string{+papillon2004 = {Proc.\ of the Papillon-2004 Workshop on Multilingual Lexical Databases}} - -@string{+riao1988 = {Proc.\ of Recherche d'Informations Assistee par Ordinateur 1988 (RIAO'88)}} - -@string{+riao2000 = {Proc.\ of Recherche d'Informations Assistee par Ordinateur 2000 (RIAO'2000)}} - -@string{+sigir1990 = {Proc.\ of 13th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'90)}} - -@string{+sigir1993 = {Proc.\ of 16th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'93)}} - -@string{+sigir1994 = {Proc.\ of 17th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'94)}} - -@string{+sigir1995 = {Proc.\ of 18th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'95)}} - -@string{+sigir1996 = {Proc.\ of 19th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'96)}} - -@string{+sigir1997 = {Proc.\ of 20th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'97)}} - -@string{+sigir1998 = {Proc.\ of 21st International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'98)}} - -@string{+sigir1999 = {Proc.\ of 22nd International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'99)}} - -@string{+sigir2000 = {Proc.\ of 23rd International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2000)}} - -@string{+sigir2001 = {Proc.\ of 24th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2001)}} - -@string{+sigsemprep2003 = {Proc.\ of the ACL-SIGSEM Workshop on the Linguistic Dimensions of Prepositions and their Use in Computational Linguistics Formalisms and Applications}} - -@string{+sigsemprep2005 = {Proc.\ of the Second ACL-SIGSEM Workshop on the Linguistic Dimensions of Prepositions and their Use in Computational Linguistics Formalisms and Applications}} - -@string{+taln1999 = {Actes de la 6e Conf\'erence annuelle sur le Traitement Automatique des Langues Naturelles (TALN '99)}} - -@string{+tmi1993 = {Proc.\ of the 5th International Conference on Theoretical and Methodological Issues in Machine Translation (TMI-93)}} - -@string{+tmi1995 = {Proc.\ of the 6th International Conference on Theoretical and Methodological Issues in Machine Translation (TMI-95)}} - -@string{+tmi1997 = {Proc.\ of the 7th International Conference on Theoretical and Methodological Issues in Machine Translation (TMI-97)}} - -@string{+tmi1999 = {Proc.\ of the 8th International Conference on Theoretical and Methodological Issues in Machine Translation (TMI-99)}} - -@string{+tmi2002 = {Proc.\ of the 9th International Conference on Theoretical and Methodological Issues in Machine Translation (TMI 2002)}} - -@string{+trec1999 = {Proc.\ of the 7th Text REtrieval Conference (TREC-7)}} - -@string{+trec2000 = {Proc.\ of the 8th Text REtrieval Conference (TREC-8)}} - -@string{+wcn1994 = {Proc.\ of the Workshop on Compound Nouns: Multilingual Aspects of Nominal Composition}} - -@string{+wmt2008 = {Proc.\ of the Third Workshop on Machine Translation}} - -@string{+wvlc1993 = {Proc.\ of the Workshop on Very Large Corpora: Academic and Industrial Perspectives}} - 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Goodman}, - Isbn = {0-591-85426-0}, - Note = {Adviser-Stuart Shieber}, - Order_No = {AAI9832377}, - Publisher = {Harvard University}, - Title = {Parsing inside-out}, - Year = {1998}} - -@inproceedings{mi08forest, - Address = {Columbus, Ohio}, - Author = {Mi, Haitao and Huang, Liang and Liu, Qun}, - Booktitle = +ACL2008, - Month = {June}, - Pages = {192--199}, - Title = {Forest-Based Translation}, - Url = {http://www.aclweb.org/anthology/P/P08/P08-1023}, - Year = {2008}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/P/P08/P08-1023}} - -@inproceedings{huang06syntax, - Address = {Boston, MA}, - Author = {Huang, Liang and Knight, Kevin and Joshi, Aravind}, - Booktitle = {In Proceedings of the 7th Biennial Conference of the Association for Machine Translation in the Americas ({AMTA})}, - Title = {Statistical Syntax-Directed Translation with Extended Domain of Locality}, - Year = {2006}} - -@inproceedings{kumar04mbr, - Author = {Shankar Kumar and William Byrne}, - Booktitle = +NAACL2004, - Pages = {169--176}, - Title = {Minimum bayes-risk decoding for statistical machine translation}, - Year = {2004}} - -@inproceedings{zhang08bitg, - Address = {Columbus, Ohio}, - Author = {Zhang, Hao and Quirk, Chris and Moore, Robert C. and Gildea, Daniel}, - Booktitle = +ACL2008, - Month = {June}, - Pages = {97--105}, - Title = {{Bayesian} Learning of Non-Compositional Phrases with Synchronous Parsing}, - Year = {2008}} - -@inproceedings{newman07distributed, - Author = {David Newman and Arthur Asuncion and Padhraic Smyth and Max Welling}, - Booktitle = {NIPS}, - Publisher = {MIT Press}, - Title = {Distributed Inference for Latent Dirichlet Allocation.}, - Year = {2007}} - -@inproceedings{asuncion08asynchronous, - Author = {Arthur Asuncion and Padhraic Smyth and Max Welling}, - Booktitle = {NIPS}, - Publisher = {MIT Press}, - Title = {Asynchronous Distributed Learning of Topic Models.}, - Year = {2008}} - -@inproceedings{johnson07, - Address = {Rochester, New York}, - Author = {Johnson, Mark and Griffiths, Thomas and Goldwater, Sharon}, - Booktitle = +NAACL2007, - Month = {April}, - Pages = {139--146}, - Title = {{Bayesian} Inference for {PCFG}s via {Markov} Chain {Monte} {Carlo}}, - Url = {http://www.aclweb.org/anthology/N/N07/N07-1018}, - Year = {2007}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/N/N07/N07-1018}} - -@inproceedings{johnson07pos, - Address = {Prague, Czech Republic}, - Author = {Johnson, Mark}, - Booktitle = +EMNLP2007, - Pages = {296--305}, - Title = {Why Doesnt {EM} Find Good {HMM} {POS}-Taggers?}, - Year = {2007}} - -@inproceedings{denero08complexity, - Address = {Columbus, Ohio}, - Author = {DeNero, John and Klein, Dan}, - Booktitle = {Proceedings of ACL-08: HLT, Short Papers}, - Month = {June}, - Pages = {25--28}, - Publisher = {Association for Computational Linguistics}, - Title = {The Complexity of Phrase Alignment Problems}, - Url = {http://www.aclweb.org/anthology/P/P08/P08-2007}, - Year = {2008}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/P/P08/P08-2007}} - -@inproceedings{denero08sampling, - Address = {Honolulu, Hawaii}, - Author = {DeNero, John and Bouchard-C\^{o}t\'{e}, Alexandre and Klein, Dan}, - Booktitle = {Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing}, - Month = {October}, - Pages = {314--323}, - Publisher = {Association for Computational Linguistics}, - Title = {Sampling Alignment Structure under a {B}ayesian Translation Model}, - Url = {http://www.aclweb.org/anthology/D08-1033}, - Year = {2008}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/D08-1033}} - -@inproceedings{birch06constraining, - Address = {New York City}, - Author = {Birch, Alexandra and Callison-Burch, Chris and Osborne, Miles and Koehn, Philipp}, - Booktitle = {Proceedings on the Workshop on Statistical Machine Translation}, - Month = {June}, - Pages = {154--157}, - Publisher = {Association for Computational Linguistics}, - Title = {Constraining the Phrase-Based, Joint Probability Statistical Translation Model}, - Url = {http://www.aclweb.org/anthology/W/W06/W06-3123}, - Year = {2006}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/W/W06/W06-3123}} - -@inproceedings{chang08chinese, - Address = {Prague, Czech Republic}, - Author = {Chang, Pi-Chuan and Jurafsky, Dan and Manning, Christopher D.}, - Booktitle = +WMT2008, - Month = {June}, - Title = {Optimizing {C}hinese Word Segmentation for Machine Translation Performance}, - Year = {2008}} - -@inproceedings{habash06preprocessing, - Address = {New York City}, - Author = {Habash, Nizar and Sadat, Fatiha}, - Booktitle = +NAACL2006, - Publisher = {Association for Computational Linguistics}, - Title = {Arabic Preprocessing Schemes for Statistical Machine Translation}, - Year = {2006}} - -@inproceedings{goldwater07, - Address = {Prague, Czech Republic}, - Author = {Goldwater, Sharon and Griffiths, Tom}, - Booktitle = +ACL2007, - Month = {June}, - Pages = {744--751}, - Title = {A fully Bayesian approach to unsupervised part-of-speech tagging}, - Url = {http://www.aclweb.org/anthology/P/P07/P07-1094}, - Year = {2007}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/P/P07/P07-1094}} - -@inproceedings{goldwater06, - Address = {Sydney}, - Author = {Goldwater, Sharon and Griffiths, Tom and Johnson, Mark}, - Booktitle = +ACL2006, - Title = {Contextual Dependencies in Unsupervised Word Segmentation}, - Year = {2006}} - -@incollection{goldwater06interpolating, - Address = {Cambridge, MA}, - Author = {Sharon Goldwater and Tom Griffiths and Mark Johnson}, - Booktitle = {Advances in Neural Information Processing Systems 18}, - Editor = {Y. Weiss and B. Sch\"{o}lkopf and J. Platt}, - Pages = {459--466}, - Publisher = {MIT Press}, - Title = {Interpolating between types and tokens by estimating power-law generators}, - Year = {2006}} - -@inproceedings{zhang08factorisation, - Address = {Manchester, UK}, - Author = {Zhang, Hao and Gildea, Daniel and Chiang, David }, - Booktitle = +COLING2008, - Pages = {1081--1088}, - Title = {Extracting Synchronous Grammar Rules From Word-Level Alignments in Linear Time}, - Year = {2008}} - -@article{antoniak74, - Author = {Antoniak, Charles E. }, - Journal = {The Annals of Statistics}, - Number = {6}, - Pages = {1152--1174}, - Title = {Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric Problems}, - Volume = {2}, - Year = {1974}} - -@phdthesis{blunsom07thesis, - Author = {Blunsom, Phil}, - School = {Department of Computer Science and Software Engineering, The University of Melbourne}, - Title = {Structured Classification for Multilingual Natural Language Processing}, - Year = {2007}} - -@phdthesis{RL:1, - Address = {Stanford, California}, - Author = {R. E. Larson}, - School = {Stanford University}, - Title = {Title of Dissertation}, - Year = 1964} - -@incollection{aldous85, - Author = {Aldous, D. }, - Booktitle = {\'{E}cole d'\'{E}t\'{e} de Probabiliti\'{e}s de Saint-Flour XIII 1983}, - Pages = {1--198}, - Publisher = {Springer}, - Title = {Exchangeability and related topics}, - Year = {1985}} - -@incollection{blunsom09scfg, - Author = {Phil Blunsom and Trevor Cohn and Miles Osborne}, - Booktitle = {Advances in Neural Information Processing Systems 21}, - Editor = {D. Koller and D. Schuurmans and Y. Bengio and L. Bottou}, - Pages = {161--168}, - Title = {Bayesian Synchronous Grammar Induction}, - Year = {2009}} - -@inproceedings{zhang06synchronous, - Author = {Zhang,, Hao and Huang,, Liang and Gildea,, Daniel and Knight,, Kevin}, - Booktitle = +NAACL2006, - Location = {New York, New York}, - Pages = {256--263}, - Title = {Synchronous binarization for machine translation}, - Year = {2006}} - -@article{fraser07measuring, - Address = {Cambridge, MA, USA}, - Author = {Fraser, Alexander and Marcu, Daniel}, - Issn = {0891-2017}, - Journal = {Computational Linguistics}, - Number = {3}, - Pages = {293--303}, - Publisher = {MIT Press}, - Title = {Measuring Word Alignment Quality for Statistical Machine Translation}, - Volume = {33}, - Year = {2007}} - -@inproceedings{teh06, - Author = {Y. Teh}, - Booktitle = {Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics}, - Pages = {985-992}, - Title = {A Hierarchical {B}ayesian Language Model based on {P}itman-{Y}or Processes}, - Year = {2006}} - -@article{ferguson73, - Author = {S. Ferguson}, - Journal = {Annals of Statistics}, - Pages = {209--230}, - Title = {A {Bayesian} Analysis of Some Nonparametric Problems}, - Volume = 1, - Year = 1973} diff --git a/report/pyp_clustering/acl09-short/common/acl-ijcnlp2009.sty b/report/pyp_clustering/acl09-short/common/acl-ijcnlp2009.sty deleted file mode 100644 index 927779a6..00000000 --- a/report/pyp_clustering/acl09-short/common/acl-ijcnlp2009.sty +++ /dev/null @@ -1,368 +0,0 @@ -% File acl-ijcnlp2009.sty -% adapted from -- -% File eacl2006.sty -% September 19, 2005 -% Contact: e.agirre@ehu.es or Sergi.Balari@uab.es - -% This is the LaTeX style file for EACL 2006. It is nearly identical to the -% style files for ACL2005, ACL 2002, ACL 2001, ACL 2000, EACL 95 and EACL -% 99. -% -% Changes made include: adapt layout to A4 and centimeters, widden abstract - -% This is the LaTeX style file for ACL 2000. It is nearly identical to the -% style files for EACL 95 and EACL 99. Minor changes include editing the -% instructions to reflect use of \documentclass rather than \documentstyle -% and removing the white space before the title on the first page -% -- John Chen, June 29, 2000 - -% To convert from submissions prepared using the style file aclsub.sty -% prepared for the ACL 2000 conference, proceed as follows: -% 1) Remove submission-specific information: \whichsession, \id, -% \wordcount, \otherconferences, \area, \keywords -% 2) \summary should be removed. The summary material should come -% after \maketitle and should be in the ``abstract'' environment -% 3) Check all citations. This style should handle citations correctly -% and also allows multiple citations separated by semicolons. -% 4) Check figures and examples. Because the final format is double- -% column, some adjustments may have to be made to fit text in the column -% or to choose full-width (\figure*} figures. -% 5) Change the style reference from aclsub to acl2000, and be sure -% this style file is in your TeX search path - - -% This is the LaTeX style file for EACL-95. It is identical to the -% style file for ANLP '94 except that the margins are adjusted for A4 -% paper. -- abney 13 Dec 94 - -% The ANLP '94 style file is a slightly modified -% version of the style used for AAAI and IJCAI, using some changes -% prepared by Fernando Pereira and others and some minor changes -% by Paul Jacobs. - -% Papers prepared using the aclsub.sty file and acl.bst bibtex style -% should be easily converted to final format using this style. -% (1) Submission information (\wordcount, \subject, and \makeidpage) -% should be removed. -% (2) \summary should be removed. The summary material should come -% after \maketitle and should be in the ``abstract'' environment -% (between \begin{abstract} and \end{abstract}). -% (3) Check all citations. This style should handle citations correctly -% and also allows multiple citations separated by semicolons. -% (4) Check figures and examples. Because the final format is double- -% column, some adjustments may have to be made to fit text in the column -% or to choose full-width (\figure*} figures. - -% Place this in a file called aclap.sty in the TeX search path. -% (Placing it in the same directory as the paper should also work.) - -% Prepared by Peter F. Patel-Schneider, liberally using the ideas of -% other style hackers, including Barbara Beeton. -% This style is NOT guaranteed to work. It is provided in the hope -% that it will make the preparation of papers easier. -% -% There are undoubtably bugs in this style. If you make bug fixes, -% improvements, etc. please let me know. My e-mail address is: -% pfps@research.att.com - -% Papers are to be prepared using the ``acl'' bibliography style, -% as follows: -% \documentclass[11pt]{article} -% \usepackage{acl2000} -% \title{Title} -% \author{Author 1 \and Author 2 \\ Address line \\ Address line \And -% Author 3 \\ Address line \\ Address line} -% \begin{document} -% ... -% \bibliography{bibliography-file} -% \bibliographystyle{acl} -% \end{document} - -% Author information can be set in various styles: -% For several authors from the same institution: -% \author{Author 1 \and ... \and Author n \\ -% Address line \\ ... \\ Address line} -% if the names do not fit well on one line use -% Author 1 \\ {\bf Author 2} \\ ... \\ {\bf Author n} \\ -% For authors from different institutions: -% \author{Author 1 \\ Address line \\ ... \\ Address line -% \And ... \And -% Author n \\ Address line \\ ... \\ Address line} -% To start a seperate ``row'' of authors use \AND, as in -% \author{Author 1 \\ Address line \\ ... \\ Address line -% \AND -% Author 2 \\ Address line \\ ... \\ Address line \And -% Author 3 \\ Address line \\ ... \\ Address line} - -% If the title and author information does not fit in the area allocated, -% place \setlength\titlebox{} right after -% \usepackage{acl2000} -% where can be something larger than 2.25in - -% \typeout{Conference Style for ACL 2000 -- released June 20, 2000} -\typeout{Conference Style for ACL 2005 -- released Octobe 11, 2004} - -% NOTE: Some laser printers have a serious problem printing TeX output. -% These printing devices, commonly known as ``write-white'' laser -% printers, tend to make characters too light. To get around this -% problem, a darker set of fonts must be created for these devices. -% - -%% % Physical page layout - slightly modified from IJCAI by pj -%% \setlength\topmargin{0.0in} \setlength\oddsidemargin{-0.0in} -%% \setlength\textheight{9.0in} \setlength\textwidth{6.5in} -%% \setlength\columnsep{0.2in} -%% \newlength\titlebox -%% \setlength\titlebox{2.25in} -%% \setlength\headheight{0pt} \setlength\headsep{0pt} -%% %\setlength\footheight{0pt} -%% \setlength\footskip{0pt} -%% \thispagestyle{empty} \pagestyle{empty} -%% \flushbottom \twocolumn \sloppy - -%% Original A4 version of page layout -%% \setlength\topmargin{-0.45cm} % changed by Rz -1.4 -%% \setlength\oddsidemargin{.8mm} % was -0cm, changed by Rz -%% \setlength\textheight{23.5cm} -%% \setlength\textwidth{15.8cm} -%% \setlength\columnsep{0.6cm} -%% \newlength\titlebox -%% \setlength\titlebox{2.00in} -%% \setlength\headheight{5pt} -%% \setlength\headsep{0pt} -%% \setlength\footheight{0pt} -%% \setlength\footskip{0pt} -%% \thispagestyle{empty} -%% \pagestyle{empty} - -% A4 modified by Eneko -\setlength{\paperwidth}{21cm} % A4 -\setlength{\paperheight}{29.7cm}% A4 -\setlength\topmargin{-0.5cm} -\setlength\oddsidemargin{0cm} -\setlength\textheight{24.7cm} -\setlength\textwidth{16.0cm} -\setlength\columnsep{0.6cm} -\newlength\titlebox -\setlength\titlebox{2.00in} -\setlength\headheight{5pt} -\setlength\headsep{0pt} -\thispagestyle{empty} -\pagestyle{empty} - - -\flushbottom \twocolumn \sloppy - -% We're never going to need a table of contents, so just flush it to -% save space --- suggested by drstrip@sandia-2 -\def\addcontentsline#1#2#3{} - -% Title stuff, taken from deproc. -\def\maketitle{\par - \begingroup - \def\thefootnote{\fnsymbol{footnote}} - \def\@makefnmark{\hbox to 0pt{$^{\@thefnmark}$\hss}} - \twocolumn[\@maketitle] \@thanks - \endgroup - \setcounter{footnote}{0} - \let\maketitle\relax \let\@maketitle\relax - \gdef\@thanks{}\gdef\@author{}\gdef\@title{}\let\thanks\relax} -\def\@maketitle{\vbox to \titlebox{\hsize\textwidth - \linewidth\hsize \vskip 0.125in minus 0.125in \centering - {\Large\bf \@title \par} \vskip 0.2in plus 1fil minus 0.1in - {\def\and{\unskip\enspace{\rm and}\enspace}% - \def\And{\end{tabular}\hss \egroup \hskip 1in plus 2fil - \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf}% - \def\AND{\end{tabular}\hss\egroup \hfil\hfil\egroup - \vskip 0.25in plus 1fil minus 0.125in - \hbox to \linewidth\bgroup\large \hfil\hfil - \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf} - \hbox to \linewidth\bgroup\large \hfil\hfil - \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf\@author - \end{tabular}\hss\egroup - \hfil\hfil\egroup} - \vskip 0.3in plus 2fil minus 0.1in -}} - -% margins for abstract -\renewenvironment{abstract}% - {\centerline{\large\bf Abstract}% - \begin{list}{}% - {\setlength{\rightmargin}{0.6cm}% - \setlength{\leftmargin}{0.6cm}}% - \item[]\ignorespaces}% - {\unskip\end{list}} - -%\renewenvironment{abstract}{\centerline{\large\bf -% Abstract}\vspace{0.5ex}\begin{quote}}{\par\end{quote}\vskip 1ex} - - -% bibliography - -\def\thebibliography#1{\section*{References} - \global\def\@listi{\leftmargin\leftmargini - \labelwidth\leftmargini \advance\labelwidth-\labelsep - \topsep 1pt plus 2pt minus 1pt - \parsep 0.25ex plus 1pt \itemsep 0.25ex plus 1pt} - \list {[\arabic{enumi}]}{\settowidth\labelwidth{[#1]}\leftmargin\labelwidth - \advance\leftmargin\labelsep\usecounter{enumi}} - \def\newblock{\hskip .11em plus .33em minus -.07em} - \sloppy - \sfcode`\.=1000\relax} - -\def\@up#1{\raise.2ex\hbox{#1}} - -% most of cite format is from aclsub.sty by SMS - -% don't box citations, separate with ; and a space -% also, make the penalty between citations negative: a good place to break -% changed comma back to semicolon pj 2/1/90 -% \def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi -% \def\@citea{}\@cite{\@for\@citeb:=#2\do -% {\@citea\def\@citea{;\penalty\@citeseppen\ }\@ifundefined -% {b@\@citeb}{{\bf ?}\@warning -% {Citation `\@citeb' on page \thepage \space undefined}}% -% {\csname b@\@citeb\endcsname}}}{#1}} - -% don't box citations, separate with ; and a space -% Replaced for multiple citations (pj) -% don't box citations and also add space, semicolon between multiple citations -\def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi - \def\@citea{}\@cite{\@for\@citeb:=#2\do - {\@citea\def\@citea{; }\@ifundefined - {b@\@citeb}{{\bf ?}\@warning - {Citation `\@citeb' on page \thepage \space undefined}}% - {\csname b@\@citeb\endcsname}}}{#1}} - -% Allow short (name-less) citations, when used in -% conjunction with a bibliography style that creates labels like -% \citename{, } -% -\let\@internalcite\cite -\def\cite{\def\citename##1{##1, }\@internalcite} -\def\shortcite{\def\citename##1{}\@internalcite} -\def\newcite{\def\citename##1{{\frenchspacing##1} (}\@internalciteb} - -% Macros for \newcite, which leaves name in running text, and is -% otherwise like \shortcite. -\def\@citexb[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi - \def\@citea{}\@newcite{\@for\@citeb:=#2\do - {\@citea\def\@citea{;\penalty\@m\ }\@ifundefined - {b@\@citeb}{{\bf ?}\@warning - {Citation `\@citeb' on page \thepage \space undefined}}% -{\csname b@\@citeb\endcsname}}}{#1}} -\def\@internalciteb{\@ifnextchar [{\@tempswatrue\@citexb}{\@tempswafalse\@citexb[]}} - -\def\@newcite#1#2{{#1\if@tempswa, #2\fi)}} - -\def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} - -%%% More changes made by SMS (originals in latex.tex) -% Use parentheses instead of square brackets in the text. -\def\@cite#1#2{({#1\if@tempswa , #2\fi})} - -% Don't put a label in the bibliography at all. Just use the unlabeled format -% instead. -\def\thebibliography#1{\vskip\parskip% -\vskip\baselineskip% -\def\baselinestretch{1}% -\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% -\vskip-\parskip% -\vskip-\baselineskip% -\section*{References\@mkboth - {References}{References}}\list - {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} - \setlength{\itemindent}{-\parindent}} - \def\newblock{\hskip .11em plus .33em minus -.07em} - \sloppy\clubpenalty4000\widowpenalty4000 - \sfcode`\.=1000\relax} -\let\endthebibliography=\endlist - -% Allow for a bibliography of sources of attested examples -\def\thesourcebibliography#1{\vskip\parskip% -\vskip\baselineskip% -\def\baselinestretch{1}% -\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% -\vskip-\parskip% -\vskip-\baselineskip% -\section*{Sources of Attested Examples\@mkboth - {Sources of Attested Examples}{Sources of Attested Examples}}\list - {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} - \setlength{\itemindent}{-\parindent}} - \def\newblock{\hskip .11em plus .33em minus -.07em} - \sloppy\clubpenalty4000\widowpenalty4000 - \sfcode`\.=1000\relax} -\let\endthesourcebibliography=\endlist - -\def\@lbibitem[#1]#2{\item[]\if@filesw - { \def\protect##1{\string ##1\space}\immediate - \write\@auxout{\string\bibcite{#2}{#1}}\fi\ignorespaces}} - -\def\@bibitem#1{\item\if@filesw \immediate\write\@auxout - {\string\bibcite{#1}{\the\c@enumi}}\fi\ignorespaces} - -% sections with less space -\def\section{\@startsection {section}{1}{\z@}{-2.0ex plus - -0.5ex minus -.2ex}{1.5ex plus 0.3ex minus .2ex}{\large\bf\raggedright}} -\def\subsection{\@startsection{subsection}{2}{\z@}{-1.8ex plus - -0.5ex minus -.2ex}{0.8ex plus .2ex}{\normalsize\bf\raggedright}} -%% changed by KO to - values to get teh initial parindent right -\def\subsubsection{\@startsection{subsubsection}{3}{\z@}{-1.5ex plus - -0.5ex minus -.2ex}{0.5ex plus .2ex}{\normalsize\bf\raggedright}} -\def\paragraph{\@startsection{paragraph}{4}{\z@}{1.5ex plus - 0.5ex minus .2ex}{-1em}{\normalsize\bf}} -\def\subparagraph{\@startsection{subparagraph}{5}{\parindent}{1.5ex plus - 0.5ex minus .2ex}{-1em}{\normalsize\bf}} - -% Footnotes -\footnotesep 6.65pt % -\skip\footins 9pt plus 4pt minus 2pt -\def\footnoterule{\kern-3pt \hrule width 5pc \kern 2.6pt } -\setcounter{footnote}{0} - -% Lists and paragraphs -\parindent 1em -\topsep 4pt plus 1pt minus 2pt -\partopsep 1pt plus 0.5pt minus 0.5pt -\itemsep 2pt plus 1pt minus 0.5pt -\parsep 2pt plus 1pt minus 0.5pt - -\leftmargin 2em \leftmargini\leftmargin \leftmarginii 2em -\leftmarginiii 1.5em \leftmarginiv 1.0em \leftmarginv .5em \leftmarginvi .5em -\labelwidth\leftmargini\advance\labelwidth-\labelsep \labelsep 5pt - -\def\@listi{\leftmargin\leftmargini} -\def\@listii{\leftmargin\leftmarginii - \labelwidth\leftmarginii\advance\labelwidth-\labelsep - \topsep 2pt plus 1pt minus 0.5pt - \parsep 1pt plus 0.5pt minus 0.5pt - \itemsep \parsep} -\def\@listiii{\leftmargin\leftmarginiii - \labelwidth\leftmarginiii\advance\labelwidth-\labelsep - \topsep 1pt plus 0.5pt minus 0.5pt - \parsep \z@ \partopsep 0.5pt plus 0pt minus 0.5pt - \itemsep \topsep} -\def\@listiv{\leftmargin\leftmarginiv - \labelwidth\leftmarginiv\advance\labelwidth-\labelsep} -\def\@listv{\leftmargin\leftmarginv - \labelwidth\leftmarginv\advance\labelwidth-\labelsep} -\def\@listvi{\leftmargin\leftmarginvi - \labelwidth\leftmarginvi\advance\labelwidth-\labelsep} - -\abovedisplayskip 7pt plus2pt minus5pt% -\belowdisplayskip \abovedisplayskip -\abovedisplayshortskip 0pt plus3pt% -\belowdisplayshortskip 4pt plus3pt minus3pt% - -% Less leading in most fonts (due to the narrow columns) -% The choices were between 1-pt and 1.5-pt leading -\def\@normalsize{\@setsize\normalsize{11pt}\xpt\@xpt} -\def\small{\@setsize\small{10pt}\ixpt\@ixpt} -\def\footnotesize{\@setsize\footnotesize{10pt}\ixpt\@ixpt} -\def\scriptsize{\@setsize\scriptsize{8pt}\viipt\@viipt} -\def\tiny{\@setsize\tiny{7pt}\vipt\@vipt} -\def\large{\@setsize\large{14pt}\xiipt\@xiipt} -\def\Large{\@setsize\Large{16pt}\xivpt\@xivpt} -\def\LARGE{\@setsize\LARGE{20pt}\xviipt\@xviipt} -\def\huge{\@setsize\huge{23pt}\xxpt\@xxpt} -\def\Huge{\@setsize\Huge{28pt}\xxvpt\@xxvpt} diff --git a/report/pyp_clustering/acl09-short/common/acl.bst b/report/pyp_clustering/acl09-short/common/acl.bst deleted file mode 100644 index 4396d4dc..00000000 --- a/report/pyp_clustering/acl09-short/common/acl.bst +++ /dev/null @@ -1,1322 +0,0 @@ - -% BibTeX `acl' style file for BibTeX version 0.99c, LaTeX version 2.09 -% This version was made by modifying `aaai-named' format based on the master -% file by Oren Patashnik (PATASHNIK@SCORE.STANFORD.EDU) - -% Copyright (C) 1985, all rights reserved. -% Modifications Copyright 1988, Peter F. Patel-Schneider -% Further modifictions by Stuart Shieber, 1991, and Fernando Pereira, 1992. -% Copying of this file is authorized only if either -% (1) you make absolutely no changes to your copy, including name, or -% (2) if you do make changes, you name it something other than -% btxbst.doc, plain.bst, unsrt.bst, alpha.bst, and abbrv.bst. -% This restriction helps ensure that all standard styles are identical. - -% There are undoubtably bugs in this style. If you make bug fixes, -% improvements, etc. please let me know. My e-mail address is: -% pfps@spar.slb.com - -% Citation format: [author-last-name, year] -% [author-last-name and author-last-name, year] -% [author-last-name {\em et al.}, year] -% -% Reference list ordering: alphabetical by author or whatever passes -% for author in the absence of one. -% -% This BibTeX style has support for short (year only) citations. This -% is done by having the citations actually look like -% \citename{name-info, }year -% The LaTeX style has to have the following -% \let\@internalcite\cite -% \def\cite{\def\citename##1{##1}\@internalcite} -% \def\shortcite{\def\citename##1{}\@internalcite} -% \def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} -% which makes \shortcite the macro for short citations. - -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% -% Changes made by SMS for thesis style -% no emphasis on "et al." -% "Ph.D." includes periods (not "PhD") -% moved year to immediately after author's name -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% -ENTRY - { address - author - booktitle - chapter - edition - editor - howpublished - institution - journal - key - month - note - number - organization - pages - publisher - school - series - title - type - volume - year - } - {} - { label extra.label sort.label } - -INTEGERS { output.state before.all mid.sentence after.sentence after.block } - -FUNCTION {init.state.consts} -{ #0 'before.all := - #1 'mid.sentence := - #2 'after.sentence := - #3 'after.block := -} - -STRINGS { s t } - -FUNCTION {output.nonnull} -{ 's := - output.state mid.sentence = - { ", " * write$ } - { output.state after.block = - { add.period$ write$ - newline$ - "\newblock " write$ - } - { output.state before.all = - 'write$ - { add.period$ " " * write$ } - if$ - } - if$ - mid.sentence 'output.state := - } - if$ - s -} - -FUNCTION {output} -{ duplicate$ empty$ - 'pop$ - 'output.nonnull - if$ -} - -FUNCTION {output.check} -{ 't := - duplicate$ empty$ - { pop$ "empty " t * " in " * cite$ * warning$ } - 'output.nonnull - if$ -} - -FUNCTION {output.bibitem} -{ newline$ - - "\bibitem[" write$ - label write$ - "]{" write$ - - cite$ write$ - "}" write$ - newline$ - "" - before.all 'output.state := -} - -FUNCTION {fin.entry} -{ add.period$ - write$ - newline$ -} - -FUNCTION {new.block} -{ output.state before.all = - 'skip$ - { after.block 'output.state := } - if$ -} - -FUNCTION {new.sentence} -{ output.state after.block = - 'skip$ - { output.state before.all = - 'skip$ - { after.sentence 'output.state := } - if$ - } - if$ -} - -FUNCTION {not} -{ { #0 } - { #1 } - if$ -} - -FUNCTION {and} -{ 'skip$ - { pop$ #0 } - if$ -} - -FUNCTION {or} -{ { pop$ #1 } - 'skip$ - if$ -} - -FUNCTION {new.block.checka} -{ empty$ - 'skip$ - 'new.block - if$ -} - -FUNCTION {new.block.checkb} -{ empty$ - swap$ empty$ - and - 'skip$ - 'new.block - if$ -} - -FUNCTION {new.sentence.checka} -{ empty$ - 'skip$ - 'new.sentence - if$ -} - -FUNCTION {new.sentence.checkb} -{ empty$ - swap$ empty$ - and - 'skip$ - 'new.sentence - if$ -} - -FUNCTION {field.or.null} -{ duplicate$ empty$ - { pop$ "" } - 'skip$ - if$ -} - -FUNCTION {emphasize} -{ duplicate$ empty$ - { pop$ "" } - { "{\em " swap$ * "}" * } - if$ -} - -INTEGERS { nameptr namesleft numnames } - -FUNCTION {format.names} -{ 's := - #1 'nameptr := - s num.names$ 'numnames := - numnames 'namesleft := - { namesleft #0 > } - - { s nameptr "{ff~}{vv~}{ll}{, jj}" format.name$ 't := - - nameptr #1 > - { namesleft #1 > - { ", " * t * } - { numnames #2 > - { "," * } - 'skip$ - if$ - t "others" = - { " et~al." * } - { " and " * t * } - if$ - } - if$ - } - 't - if$ - nameptr #1 + 'nameptr := - namesleft #1 - 'namesleft := - } - while$ -} - -FUNCTION {format.authors} -{ author empty$ - { "" } - { author format.names } - if$ -} - -FUNCTION {format.editors} -{ editor empty$ - { "" } - { editor format.names - editor num.names$ #1 > - { ", editors" * } - { ", editor" * } - if$ - } - if$ -} - -FUNCTION {format.title} -{ title empty$ - { "" } - - { title "t" change.case$ } - - if$ -} - -FUNCTION {n.dashify} -{ 't := - "" - { t empty$ not } - { t #1 #1 substring$ "-" = - { t #1 #2 substring$ "--" = not - { "--" * - t #2 global.max$ substring$ 't := - } - { { t #1 #1 substring$ "-" = } - { "-" * - t #2 global.max$ substring$ 't := - } - while$ - } - if$ - } - { t #1 #1 substring$ * - t #2 global.max$ substring$ 't := - } - if$ - } - while$ -} - -FUNCTION {format.date} -{ year empty$ - { month empty$ - { "" } - { "there's a month but no year in " cite$ * warning$ - month - } - if$ - } - { month empty$ - { "" } - { month } - if$ - } - if$ -} - -FUNCTION {format.btitle} -{ title emphasize -} - -FUNCTION {tie.or.space.connect} -{ duplicate$ text.length$ #3 < - { "~" } - { " " } - if$ - swap$ * * -} - -FUNCTION {either.or.check} -{ empty$ - 'pop$ - { "can't use both " swap$ * " fields in " * cite$ * warning$ } - if$ -} - -FUNCTION {format.bvolume} -{ volume empty$ - { "" } - { "volume" volume tie.or.space.connect - series empty$ - 'skip$ - { " of " * series emphasize * } - if$ - "volume and number" number either.or.check - } - if$ -} - -FUNCTION {format.number.series} -{ volume empty$ - { number empty$ - { series field.or.null } - { output.state mid.sentence = - { "number" } - { "Number" } - if$ - number tie.or.space.connect - series empty$ - { "there's a number but no series in " cite$ * warning$ } - { " in " * series * } - if$ - } - if$ - } - { "" } - if$ -} - -FUNCTION {format.edition} -{ edition empty$ - { "" } - { output.state mid.sentence = - { edition "l" change.case$ " edition" * } - { edition "t" change.case$ " edition" * } - if$ - } - if$ -} - -INTEGERS { multiresult } - -FUNCTION {multi.page.check} -{ 't := - #0 'multiresult := - { multiresult not - t empty$ not - and - } - { t #1 #1 substring$ - duplicate$ "-" = - swap$ duplicate$ "," = - swap$ "+" = - or or - { #1 'multiresult := } - { t #2 global.max$ substring$ 't := } - if$ - } - while$ - multiresult -} - -FUNCTION {format.pages} -{ pages empty$ - { "" } - { pages multi.page.check - { "pages" pages n.dashify tie.or.space.connect } - { "page" pages tie.or.space.connect } - if$ - } - if$ -} - -FUNCTION {format.year.label} -{ year extra.label * -} - -FUNCTION {format.vol.num.pages} -{ volume field.or.null - number empty$ - 'skip$ - { "(" number * ")" * * - volume empty$ - { "there's a number but no volume in " cite$ * warning$ } - 'skip$ - if$ - } - if$ - pages empty$ - 'skip$ - { duplicate$ empty$ - { pop$ format.pages } - { ":" * pages n.dashify * } - if$ - } - if$ -} - -FUNCTION {format.chapter.pages} -{ chapter empty$ - 'format.pages - { type empty$ - { "chapter" } - { type "l" change.case$ } - if$ - chapter tie.or.space.connect - pages empty$ - 'skip$ - { ", " * format.pages * } - if$ - } - if$ -} - -FUNCTION {format.in.ed.booktitle} -{ booktitle empty$ - { "" } - { editor empty$ - { "In " booktitle emphasize * } - { "In " format.editors * ", " * booktitle emphasize * } - if$ - } - if$ -} - -FUNCTION {empty.misc.check} -{ author empty$ title empty$ howpublished empty$ - month empty$ year empty$ note empty$ - and and and and and - - key empty$ not and - - { "all relevant fields are empty in " cite$ * warning$ } - 'skip$ - if$ -} - -FUNCTION {format.thesis.type} -{ type empty$ - 'skip$ - { pop$ - type "t" change.case$ - } - if$ -} - -FUNCTION {format.tr.number} -{ type empty$ - { "Technical Report" } - 'type - if$ - number empty$ - { "t" change.case$ } - { number tie.or.space.connect } - if$ -} - -FUNCTION {format.article.crossref} -{ key empty$ - { journal empty$ - { "need key or journal for " cite$ * " to crossref " * crossref * - warning$ - "" - } - { "In {\em " journal * "\/}" * } - if$ - } - { "In " key * } - if$ - " \cite{" * crossref * "}" * -} - -FUNCTION {format.crossref.editor} -{ editor #1 "{vv~}{ll}" format.name$ - editor num.names$ duplicate$ - #2 > - { pop$ " et~al." * } - { #2 < - 'skip$ - { editor #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" = - { " et~al." * } - { " and " * editor #2 "{vv~}{ll}" format.name$ * } - if$ - } - if$ - } - if$ -} - -FUNCTION {format.book.crossref} -{ volume empty$ - { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ - "In " - } - { "Volume" volume tie.or.space.connect - " of " * - } - if$ - editor empty$ - editor field.or.null author field.or.null = - or - { key empty$ - { series empty$ - { "need editor, key, or series for " cite$ * " to crossref " * - crossref * warning$ - "" * - } - { "{\em " * series * "\/}" * } - if$ - } - { key * } - if$ - } - { format.crossref.editor * } - if$ - " \cite{" * crossref * "}" * -} - -FUNCTION {format.incoll.inproc.crossref} -{ editor empty$ - editor field.or.null author field.or.null = - or - { key empty$ - { booktitle empty$ - { "need editor, key, or booktitle for " cite$ * " to crossref " * - crossref * warning$ - "" - } - { "In {\em " booktitle * "\/}" * } - if$ - } - { "In " key * } - if$ - } - { "In " format.crossref.editor * } - if$ - " \cite{" * crossref * "}" * -} - -FUNCTION {article} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - crossref missing$ - { journal emphasize "journal" output.check - format.vol.num.pages output - format.date output - } - { format.article.crossref output.nonnull - format.pages output - } - if$ - new.block - note output - fin.entry -} - -FUNCTION {book} -{ output.bibitem - author empty$ - { format.editors "author and editor" output.check } - { format.authors output.nonnull - crossref missing$ - { "author and editor" editor either.or.check } - 'skip$ - if$ - } - if$ - new.block - format.year.label "year" output.check - new.block - format.btitle "title" output.check - crossref missing$ - { format.bvolume output - new.block - format.number.series output - new.sentence - publisher "publisher" output.check - address output - } - { new.block - format.book.crossref output.nonnull - } - if$ - format.edition output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {booklet} -{ output.bibitem - format.authors output - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - howpublished address new.block.checkb - howpublished output - address output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {inbook} -{ output.bibitem - author empty$ - { format.editors "author and editor" output.check } - { format.authors output.nonnull - crossref missing$ - { "author and editor" editor either.or.check } - 'skip$ - if$ - } - if$ - format.year.label "year" output.check - new.block - new.block - format.btitle "title" output.check - crossref missing$ - { format.bvolume output - format.chapter.pages "chapter and pages" output.check - new.block - format.number.series output - new.sentence - publisher "publisher" output.check - address output - } - { format.chapter.pages "chapter and pages" output.check - new.block - format.book.crossref output.nonnull - } - if$ - format.edition output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {incollection} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - crossref missing$ - { format.in.ed.booktitle "booktitle" output.check - format.bvolume output - format.number.series output - format.chapter.pages output - new.sentence - publisher "publisher" output.check - address output - format.edition output - format.date output - } - { format.incoll.inproc.crossref output.nonnull - format.chapter.pages output - } - if$ - new.block - note output - fin.entry -} - -FUNCTION {inproceedings} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - crossref missing$ - { format.in.ed.booktitle "booktitle" output.check - format.bvolume output - format.number.series output - format.pages output - address empty$ - { organization publisher new.sentence.checkb - organization output - publisher output - format.date output - } - { address output.nonnull - format.date output - new.sentence - organization output - publisher output - } - if$ - } - { format.incoll.inproc.crossref output.nonnull - format.pages output - } - if$ - new.block - note output - fin.entry -} - -FUNCTION {conference} { inproceedings } - -FUNCTION {manual} -{ output.bibitem - author empty$ - { organization empty$ - 'skip$ - { organization output.nonnull - address output - } - if$ - } - { format.authors output.nonnull } - if$ - format.year.label "year" output.check - new.block - new.block - format.btitle "title" output.check - author empty$ - { organization empty$ - { address new.block.checka - address output - } - 'skip$ - if$ - } - { organization address new.block.checkb - organization output - address output - } - if$ - format.edition output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {mastersthesis} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - "Master's thesis" format.thesis.type output.nonnull - school "school" output.check - address output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {misc} -{ output.bibitem - format.authors output - new.block - format.year.label output - new.block - title howpublished new.block.checkb - format.title output - howpublished new.block.checka - howpublished output - format.date output - new.block - note output - fin.entry - empty.misc.check -} - -FUNCTION {phdthesis} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.btitle "title" output.check - new.block - "{Ph.D.} thesis" format.thesis.type output.nonnull - school "school" output.check - address output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {proceedings} -{ output.bibitem - editor empty$ - { organization output } - { format.editors output.nonnull } - if$ - new.block - format.year.label "year" output.check - new.block - format.btitle "title" output.check - format.bvolume output - format.number.series output - address empty$ - { editor empty$ - { publisher new.sentence.checka } - { organization publisher new.sentence.checkb - organization output - } - if$ - publisher output - format.date output - } - { address output.nonnull - format.date output - new.sentence - editor empty$ - 'skip$ - { organization output } - if$ - publisher output - } - if$ - new.block - note output - fin.entry -} - -FUNCTION {techreport} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - format.tr.number output.nonnull - institution "institution" output.check - address output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {unpublished} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - note "note" output.check - format.date output - fin.entry -} - -FUNCTION {default.type} { misc } - -MACRO {jan} {"January"} - -MACRO {feb} {"February"} - -MACRO {mar} {"March"} - -MACRO {apr} {"April"} - -MACRO {may} {"May"} - -MACRO {jun} {"June"} - -MACRO {jul} {"July"} - -MACRO {aug} {"August"} - -MACRO {sep} {"September"} - -MACRO {oct} {"October"} - -MACRO {nov} {"November"} - -MACRO {dec} {"December"} - -MACRO {acmcs} {"ACM Computing Surveys"} - -MACRO {acta} {"Acta Informatica"} - -MACRO {cacm} {"Communications of the ACM"} - -MACRO {ibmjrd} {"IBM Journal of Research and Development"} - -MACRO {ibmsj} {"IBM Systems Journal"} - -MACRO {ieeese} {"IEEE Transactions on Software Engineering"} - -MACRO {ieeetc} {"IEEE Transactions on Computers"} - -MACRO {ieeetcad} - {"IEEE Transactions on Computer-Aided Design of Integrated Circuits"} - -MACRO {ipl} {"Information Processing Letters"} - -MACRO {jacm} {"Journal of the ACM"} - -MACRO {jcss} {"Journal of Computer and System Sciences"} - -MACRO {scp} {"Science of Computer Programming"} - -MACRO {sicomp} {"SIAM Journal on Computing"} - -MACRO {tocs} {"ACM Transactions on Computer Systems"} - -MACRO {tods} {"ACM Transactions on Database Systems"} - -MACRO {tog} {"ACM Transactions on Graphics"} - -MACRO {toms} {"ACM Transactions on Mathematical Software"} - -MACRO {toois} {"ACM Transactions on Office Information Systems"} - -MACRO {toplas} {"ACM Transactions on Programming Languages and Systems"} - -MACRO {tcs} {"Theoretical Computer Science"} - -READ - -FUNCTION {sortify} -{ purify$ - "l" change.case$ -} - -INTEGERS { len } - -FUNCTION {chop.word} -{ 's := - 'len := - s #1 len substring$ = - { s len #1 + global.max$ substring$ } - 's - if$ -} - -INTEGERS { et.al.char.used } - -FUNCTION {initialize.et.al.char.used} -{ #0 'et.al.char.used := -} - -EXECUTE {initialize.et.al.char.used} - -FUNCTION {format.lab.names} -{ 's := - s num.names$ 'numnames := - - numnames #1 = - { s #1 "{vv }{ll}" format.name$ } - { numnames #2 = - { s #1 "{vv }{ll }and " format.name$ s #2 "{vv }{ll}" format.name$ * - } - { s #1 "{vv }{ll }\bgroup et al.\egroup " format.name$ } - if$ - } - if$ - -} - -FUNCTION {author.key.label} -{ author empty$ - { key empty$ - - { cite$ #1 #3 substring$ } - - { key #3 text.prefix$ } - if$ - } - { author format.lab.names } - if$ -} - -FUNCTION {author.editor.key.label} -{ author empty$ - { editor empty$ - { key empty$ - - { cite$ #1 #3 substring$ } - - { key #3 text.prefix$ } - if$ - } - { editor format.lab.names } - if$ - } - { author format.lab.names } - if$ -} - -FUNCTION {author.key.organization.label} -{ author empty$ - { key empty$ - { organization empty$ - - { cite$ #1 #3 substring$ } - - { "The " #4 organization chop.word #3 text.prefix$ } - if$ - } - { key #3 text.prefix$ } - if$ - } - { author format.lab.names } - if$ -} - -FUNCTION {editor.key.organization.label} -{ editor empty$ - { key empty$ - { organization empty$ - - { cite$ #1 #3 substring$ } - - { "The " #4 organization chop.word #3 text.prefix$ } - if$ - } - { key #3 text.prefix$ } - if$ - } - { editor format.lab.names } - if$ -} - -FUNCTION {calc.label} -{ type$ "book" = - type$ "inbook" = - or - 'author.editor.key.label - { type$ "proceedings" = - 'editor.key.organization.label - { type$ "manual" = - 'author.key.organization.label - 'author.key.label - if$ - } - if$ - } - if$ - duplicate$ - - "\protect\citename{" swap$ * "}" * - year field.or.null purify$ * - 'label := - year field.or.null purify$ * - - sortify 'sort.label := -} - -FUNCTION {sort.format.names} -{ 's := - #1 'nameptr := - "" - s num.names$ 'numnames := - numnames 'namesleft := - { namesleft #0 > } - { nameptr #1 > - { " " * } - 'skip$ - if$ - - s nameptr "{vv{ } }{ll{ }}{ ff{ }}{ jj{ }}" format.name$ 't := - - nameptr numnames = t "others" = and - { "et al" * } - { t sortify * } - if$ - nameptr #1 + 'nameptr := - namesleft #1 - 'namesleft := - } - while$ -} - -FUNCTION {sort.format.title} -{ 't := - "A " #2 - "An " #3 - "The " #4 t chop.word - chop.word - chop.word - sortify - #1 global.max$ substring$ -} - -FUNCTION {author.sort} -{ author empty$ - { key empty$ - { "to sort, need author or key in " cite$ * warning$ - "" - } - { key sortify } - if$ - } - { author sort.format.names } - if$ -} - -FUNCTION {author.editor.sort} -{ author empty$ - { editor empty$ - { key empty$ - { "to sort, need author, editor, or key in " cite$ * warning$ - "" - } - { key sortify } - if$ - } - { editor sort.format.names } - if$ - } - { author sort.format.names } - if$ -} - -FUNCTION {author.organization.sort} -{ author empty$ - { organization empty$ - { key empty$ - { "to sort, need author, organization, or key in " cite$ * warning$ - "" - } - { key sortify } - if$ - } - { "The " #4 organization chop.word sortify } - if$ - } - { author sort.format.names } - if$ -} - -FUNCTION {editor.organization.sort} -{ editor empty$ - { organization empty$ - { key empty$ - { "to sort, need editor, organization, or key in " cite$ * warning$ - "" - } - { key sortify } - if$ - } - { "The " #4 organization chop.word sortify } - if$ - } - { editor sort.format.names } - if$ -} - -FUNCTION {presort} - -{ calc.label - sort.label - " " - * - type$ "book" = - - type$ "inbook" = - or - 'author.editor.sort - { type$ "proceedings" = - 'editor.organization.sort - { type$ "manual" = - 'author.organization.sort - 'author.sort - if$ - } - if$ - } - if$ - - * - - " " - * - year field.or.null sortify - * - " " - * - title field.or.null - sort.format.title - * - #1 entry.max$ substring$ - 'sort.key$ := -} - -ITERATE {presort} - -SORT - -STRINGS { longest.label last.sort.label next.extra } - -INTEGERS { longest.label.width last.extra.num } - -FUNCTION {initialize.longest.label} -{ "" 'longest.label := - #0 int.to.chr$ 'last.sort.label := - "" 'next.extra := - #0 'longest.label.width := - #0 'last.extra.num := -} - -FUNCTION {forward.pass} -{ last.sort.label sort.label = - { last.extra.num #1 + 'last.extra.num := - last.extra.num int.to.chr$ 'extra.label := - } - { "a" chr.to.int$ 'last.extra.num := - "" 'extra.label := - sort.label 'last.sort.label := - } - if$ -} - -FUNCTION {reverse.pass} -{ next.extra "b" = - { "a" 'extra.label := } - 'skip$ - if$ - label extra.label * 'label := - label width$ longest.label.width > - { label 'longest.label := - label width$ 'longest.label.width := - } - 'skip$ - if$ - extra.label 'next.extra := -} - -EXECUTE {initialize.longest.label} - -ITERATE {forward.pass} - -REVERSE {reverse.pass} - -FUNCTION {begin.bib} - -{ et.al.char.used - { "\newcommand{\etalchar}[1]{$^{#1}$}" write$ newline$ } - 'skip$ - if$ - preamble$ empty$ - - 'skip$ - { preamble$ write$ newline$ } - if$ - - "\begin{thebibliography}{" "}" * write$ newline$ - -} - -EXECUTE {begin.bib} - -EXECUTE {init.state.consts} - -ITERATE {call.type$} - -FUNCTION {end.bib} -{ newline$ - "\end{thebibliography}" write$ newline$ -} - -EXECUTE {end.bib} - diff --git a/report/pyp_clustering/acl09-short/common/acl08.sty b/report/pyp_clustering/acl09-short/common/acl08.sty deleted file mode 100644 index 358f6d27..00000000 --- a/report/pyp_clustering/acl09-short/common/acl08.sty +++ /dev/null @@ -1,344 +0,0 @@ -% File acl2005.sty -% October 11, 2004 -% Contact: oflazer@sabanciuniv.edu - -% This is the LaTeX style file for ACL 2005. It is nearly identical to the -% style files for ACL 2002, ACL 2001, ACL 2000, EACL 95 and EACL -% 99. -% - -% This is the LaTeX style file for ACL 2000. It is nearly identical to the -% style files for EACL 95 and EACL 99. Minor changes include editing the -% instructions to reflect use of \documentclass rather than \documentstyle -% and removing the white space before the title on the first page -% -- John Chen, June 29, 2000 - -% To convert from submissions prepared using the style file aclsub.sty -% prepared for the ACL 2000 conference, proceed as follows: -% 1) Remove submission-specific information: \whichsession, \id, -% \wordcount, \otherconferences, \area, \keywords -% 2) \summary should be removed. The summary material should come -% after \maketitle and should be in the ``abstract'' environment -% 3) Check all citations. This style should handle citations correctly -% and also allows multiple citations separated by semicolons. -% 4) Check figures and examples. Because the final format is double- -% column, some adjustments may have to be made to fit text in the column -% or to choose full-width (\figure*} figures. -% 5) Change the style reference from aclsub to acl2000, and be sure -% this style file is in your TeX search path - - -% This is the LaTeX style file for EACL-95. It is identical to the -% style file for ANLP '94 except that the margins are adjusted for A4 -% paper. -- abney 13 Dec 94 - -% The ANLP '94 style file is a slightly modified -% version of the style used for AAAI and IJCAI, using some changes -% prepared by Fernando Pereira and others and some minor changes -% by Paul Jacobs. - -% Papers prepared using the aclsub.sty file and acl.bst bibtex style -% should be easily converted to final format using this style. -% (1) Submission information (\wordcount, \subject, and \makeidpage) -% should be removed. -% (2) \summary should be removed. The summary material should come -% after \maketitle and should be in the ``abstract'' environment -% (between \begin{abstract} and \end{abstract}). -% (3) Check all citations. This style should handle citations correctly -% and also allows multiple citations separated by semicolons. -% (4) Check figures and examples. Because the final format is double- -% column, some adjustments may have to be made to fit text in the column -% or to choose full-width (\figure*} figures. - -% Place this in a file called aclap.sty in the TeX search path. -% (Placing it in the same directory as the paper should also work.) - -% Prepared by Peter F. Patel-Schneider, liberally using the ideas of -% other style hackers, including Barbara Beeton. -% This style is NOT guaranteed to work. It is provided in the hope -% that it will make the preparation of papers easier. -% -% There are undoubtably bugs in this style. If you make bug fixes, -% improvements, etc. please let me know. My e-mail address is: -% pfps@research.att.com - -% Papers are to be prepared using the ``acl'' bibliography style, -% as follows: -% \documentclass[11pt]{article} -% \usepackage{acl2000} -% \title{Title} -% \author{Author 1 \and Author 2 \\ Address line \\ Address line \And -% Author 3 \\ Address line \\ Address line} -% \begin{document} -% ... -% \bibliography{bibliography-file} -% \bibliographystyle{acl} -% \end{document} - -% Author information can be set in various styles: -% For several authors from the same institution: -% \author{Author 1 \and ... \and Author n \\ -% Address line \\ ... \\ Address line} -% if the names do not fit well on one line use -% Author 1 \\ {\bf Author 2} \\ ... \\ {\bf Author n} \\ -% For authors from different institutions: -% \author{Author 1 \\ Address line \\ ... \\ Address line -% \And ... \And -% Author n \\ Address line \\ ... \\ Address line} -% To start a seperate ``row'' of authors use \AND, as in -% \author{Author 1 \\ Address line \\ ... \\ Address line -% \AND -% Author 2 \\ Address line \\ ... \\ Address line \And -% Author 3 \\ Address line \\ ... \\ Address line} - -% If the title and author information does not fit in the area allocated, -% place \setlength\titlebox{} right after -% \usepackage{acl2000} -% where can be something larger than 2.25in - -% \typeout{Conference Style for ACL 2000 -- released June 20, 2000} -\typeout{Conference Style for ACL 2005 -- released Octobe 11, 2004} - -% NOTE: Some laser printers have a serious problem printing TeX output. -% These printing devices, commonly known as ``write-white'' laser -% printers, tend to make characters too light. To get around this -% problem, a darker set of fonts must be created for these devices. -% - -% Physical page layout - slightly modified from IJCAI by pj -\setlength\topmargin{0.0in} \setlength\oddsidemargin{-0.0in} -\setlength\textheight{9.0in} \setlength\textwidth{6.5in} -\setlength\columnsep{0.2in} -\newlength\titlebox -\setlength\titlebox{2.25in} -\setlength\headheight{0pt} \setlength\headsep{0pt} -%\setlength\footheight{0pt} -\setlength\footskip{0pt} -\thispagestyle{empty} \pagestyle{empty} -\flushbottom \twocolumn \sloppy - -%% A4 version of page layout -%\setlength\topmargin{-0.45cm} % changed by Rz -1.4 -%\setlength\oddsidemargin{.8mm} % was -0cm, changed by Rz -%\setlength\textheight{23.5cm} -%\setlength\textwidth{15.8cm} -%\setlength\columnsep{0.6cm} -%\newlength\titlebox -%\setlength\titlebox{2.00in} -%\setlength\headheight{5pt} -%\setlength\headsep{0pt} -%%\setlength\footheight{0pt} -%\setlength\footskip{0pt} -%\thispagestyle{empty} -%\pagestyle{empty} - -\flushbottom \twocolumn \sloppy - -% We're never going to need a table of contents, so just flush it to -% save space --- suggested by drstrip@sandia-2 -\def\addcontentsline#1#2#3{} - -% Title stuff, taken from deproc. -\def\maketitle{\par - \begingroup - \def\thefootnote{\fnsymbol{footnote}} - \def\@makefnmark{\hbox to 0pt{$^{\@thefnmark}$\hss}} - \twocolumn[\@maketitle] \@thanks - \endgroup - \setcounter{footnote}{0} - \let\maketitle\relax \let\@maketitle\relax - \gdef\@thanks{}\gdef\@author{}\gdef\@title{}\let\thanks\relax} -\def\@maketitle{\vbox to \titlebox{\hsize\textwidth - \linewidth\hsize \vskip 0.125in minus 0.125in \centering - {\Large\bf \@title \par} \vskip 0.2in plus 1fil minus 0.1in - {\def\and{\unskip\enspace{\rm and}\enspace}% - \def\And{\end{tabular}\hss \egroup \hskip 1in plus 2fil - \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf}% - \def\AND{\end{tabular}\hss\egroup \hfil\hfil\egroup - \vskip 0.25in plus 1fil minus 0.125in - \hbox to \linewidth\bgroup\large \hfil\hfil - \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf} - \hbox to \linewidth\bgroup\large \hfil\hfil - \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf\@author - \end{tabular}\hss\egroup - \hfil\hfil\egroup} - \vskip 0.3in plus 2fil minus 0.1in -}} -\renewenvironment{abstract}{\centerline{\large\bf - Abstract}\vspace{0.5ex}\begin{quote} \small}{\par\end{quote}\vskip 1ex} - - -% bibliography - -\def\thebibliography#1{\section*{References} - \global\def\@listi{\leftmargin\leftmargini - \labelwidth\leftmargini \advance\labelwidth-\labelsep - \topsep 1pt plus 2pt minus 1pt - \parsep 0.25ex plus 1pt \itemsep 0.25ex plus 1pt} - \list {[\arabic{enumi}]}{\settowidth\labelwidth{[#1]}\leftmargin\labelwidth - \advance\leftmargin\labelsep\usecounter{enumi}} - \def\newblock{\hskip .11em plus .33em minus -.07em} - \sloppy - \sfcode`\.=1000\relax} - -\def\@up#1{\raise.2ex\hbox{#1}} - -% most of cite format is from aclsub.sty by SMS - -% don't box citations, separate with ; and a space -% also, make the penalty between citations negative: a good place to break -% changed comma back to semicolon pj 2/1/90 -% \def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi -% \def\@citea{}\@cite{\@for\@citeb:=#2\do -% {\@citea\def\@citea{;\penalty\@citeseppen\ }\@ifundefined -% {b@\@citeb}{{\bf ?}\@warning -% {Citation `\@citeb' on page \thepage \space undefined}}% -% {\csname b@\@citeb\endcsname}}}{#1}} - -% don't box citations, separate with ; and a space -% Replaced for multiple citations (pj) -% don't box citations and also add space, semicolon between multiple citations -\def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi - \def\@citea{}\@cite{\@for\@citeb:=#2\do - {\@citea\def\@citea{; }\@ifundefined - {b@\@citeb}{{\bf ?}\@warning - {Citation `\@citeb' on page \thepage \space undefined}}% - {\csname b@\@citeb\endcsname}}}{#1}} - -% Allow short (name-less) citations, when used in -% conjunction with a bibliography style that creates labels like -% \citename{, } -% -\let\@internalcite\cite -\def\cite{\def\citename##1{##1, }\@internalcite} -\def\shortcite{\def\citename##1{}\@internalcite} -\def\newcite{\def\citename##1{{\frenchspacing##1} (}\@internalciteb} - -% Macros for \newcite, which leaves name in running text, and is -% otherwise like \shortcite. -\def\@citexb[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi - \def\@citea{}\@newcite{\@for\@citeb:=#2\do - {\@citea\def\@citea{;\penalty\@m\ }\@ifundefined - {b@\@citeb}{{\bf ?}\@warning - {Citation `\@citeb' on page \thepage \space undefined}}% -{\csname b@\@citeb\endcsname}}}{#1}} -\def\@internalciteb{\@ifnextchar [{\@tempswatrue\@citexb}{\@tempswafalse\@citexb[]}} - -\def\@newcite#1#2{{#1\if@tempswa, #2\fi)}} - -\def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} - -%%% More changes made by SMS (originals in latex.tex) -% Use parentheses instead of square brackets in the text. -\def\@cite#1#2{({#1\if@tempswa , #2\fi})} - -% Don't put a label in the bibliography at all. Just use the unlabeled format -% instead. -\def\thebibliography#1{\small\vskip\parskip% -\vskip\baselineskip% -\def\baselinestretch{1}% -\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% -\vskip-\parskip% -\vskip-\baselineskip% -\section*{References\@mkboth - {References}{References}}\list - {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} - \setlength{\itemsep}{-0.5ex} - \setlength{\itemindent}{-\parindent}} - \def\newblock{\hskip .11em plus .33em minus -.07em} - \sloppy\clubpenalty4000\widowpenalty4000 - \sfcode`\.=1000\relax} -\let\endthebibliography=\endlist - -% Allow for a bibliography of sources of attested examples -\def\thesourcebibliography#1{\vskip\parskip% -\vskip\baselineskip% -\def\baselinestretch{1}% -\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% -\vskip-\parskip% -\vskip-\baselineskip% -\section*{Sources of Attested Examples\@mkboth - {Sources of Attested Examples}{Sources of Attested Examples}}\list - {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} - \setlength{\itemindent}{-\parindent}} - \def\newblock{\hskip .11em plus .33em minus -.07em} - \sloppy\clubpenalty4000\widowpenalty4000 - \sfcode`\.=1000\relax} -\let\endthesourcebibliography=\endlist - -\def\@lbibitem[#1]#2{\item[]\if@filesw - { \def\protect##1{\string ##1\space}\immediate - \write\@auxout{\string\bibcite{#2}{#1}}\fi\ignorespaces}} - -\def\@bibitem#1{\item\if@filesw \immediate\write\@auxout - {\string\bibcite{#1}{\the\c@enumi}}\fi\ignorespaces} - -% sections with less space -\def\section{\@startsection {section}{1}{\z@}{-2.0ex plus - -0.5ex minus -.2ex}{1.5ex plus 0.3ex minus .2ex}{\large\bf\raggedright}} -\def\subsection{\@startsection{subsection}{2}{\z@}{-1.8ex plus - -0.5ex minus -.2ex}{0.8ex plus .2ex}{\normalsize\bf\raggedright}} -\def\subsubsection{\@startsection{subsubsection}{3}{\z@}{1.5ex plus - 0.5ex minus .2ex}{0.5ex plus .2ex}{\normalsize\bf\raggedright}} -\def\paragraph{\@startsection{paragraph}{4}{\z@}{1.5ex plus - 0.5ex minus .2ex}{-1em}{\normalsize\bf}} -\def\subparagraph{\@startsection{subparagraph}{5}{\parindent}{1.5ex plus - 0.5ex minus .2ex}{-1em}{\normalsize\bf}} - -% Footnotes -\footnotesep 6.65pt % -\skip\footins 9pt plus 4pt minus 2pt -\def\footnoterule{\kern-3pt \hrule width 5pc \kern 2.6pt } -\setcounter{footnote}{0} - -% Lists and paragraphs -\parindent 1em -\topsep 4pt plus 1pt minus 2pt -\partopsep 1pt plus 0.5pt minus 0.5pt -\itemsep 2pt plus 1pt minus 0.5pt -\parsep 2pt plus 1pt minus 0.5pt - -\leftmargin 2em \leftmargini\leftmargin \leftmarginii 2em -\leftmarginiii 1.5em \leftmarginiv 1.0em \leftmarginv .5em \leftmarginvi .5em -\labelwidth\leftmargini\advance\labelwidth-\labelsep \labelsep 5pt - -\def\@listi{\leftmargin\leftmargini} -\def\@listii{\leftmargin\leftmarginii - \labelwidth\leftmarginii\advance\labelwidth-\labelsep - \topsep 2pt plus 1pt minus 0.5pt - \parsep 1pt plus 0.5pt minus 0.5pt - \itemsep \parsep} -\def\@listiii{\leftmargin\leftmarginiii - \labelwidth\leftmarginiii\advance\labelwidth-\labelsep - \topsep 1pt plus 0.5pt minus 0.5pt - \parsep \z@ \partopsep 0.5pt plus 0pt minus 0.5pt - \itemsep \topsep} -\def\@listiv{\leftmargin\leftmarginiv - \labelwidth\leftmarginiv\advance\labelwidth-\labelsep} -\def\@listv{\leftmargin\leftmarginv - \labelwidth\leftmarginv\advance\labelwidth-\labelsep} -\def\@listvi{\leftmargin\leftmarginvi - \labelwidth\leftmarginvi\advance\labelwidth-\labelsep} - -\abovedisplayskip 7pt plus2pt minus5pt% -\belowdisplayskip \abovedisplayskip -\abovedisplayshortskip 0pt plus3pt% -\belowdisplayshortskip 4pt plus3pt minus3pt% - -% Less leading in most fonts (due to the narrow columns) -% The choices were between 1-pt and 1.5-pt leading -%\def\@normalsize{\@setsize\normalsize{11pt}\xpt\@xpt} -%\def\small{\@setsize\small{10pt}\ixpt\@ixpt} -%\def\footnotesize{\@setsize\footnotesize{10pt}\ixpt\@ixpt} -%\def\scriptsize{\@setsize\scriptsize{8pt}\viipt\@viipt} -%\def\tiny{\@setsize\tiny{7pt}\vipt\@vipt} -%\def\large{\@setsize\large{14pt}\xiipt\@xiipt} -%\def\Large{\@setsize\Large{16pt}\xivpt\@xivpt} -%\def\LARGE{\@setsize\LARGE{20pt}\xviipt\@xviipt} -%\def\huge{\@setsize\huge{23pt}\xxpt\@xxpt} -%\def\Huge{\@setsize\Huge{28pt}\xxvpt\@xxvpt} - -\let\@@makecaption\@makecaption -\renewcommand{\@makecaption}[1]{\@@makecaption{\small #1}} - -\newcommand{\Thanks}[1]{\thanks{\ #1}} \ No newline at end of file diff --git a/report/pyp_clustering/acl09-short/common/algorithmicx.sty b/report/pyp_clustering/acl09-short/common/algorithmicx.sty deleted file mode 100644 index bfb7daba..00000000 --- a/report/pyp_clustering/acl09-short/common/algorithmicx.sty +++ /dev/null @@ -1,786 +0,0 @@ -% ALGORITHMIC STYLE -- Released 27 APR 2005 -% for LaTeX version 2e -% -% Copyright Szasz Janos -% E-mail szaszjanos@users.sourceforge.net -% -% -% *** INITIALISING *** -% -% -\NeedsTeXFormat{LaTeX2e} -\ProvidesPackage{algorithmicx}[2005/04/27 v1.2 Algorithmicx] -\RequirePackage{ifthen} -\typeout{Document Style algorithmicx 1.2 - a greatly improved `algorithmic' style} -% -\newcounter{ALG@line} -\newcounter{ALG@rem} -\newcounter{ALG@nested} -\newlength{\ALG@tlm} -\newlength{\ALG@thistlm} -\newcounter{ALG@Lnr}% the number of defined languages -\setcounter{ALG@Lnr}{0} -\newcounter{ALG@blocknr}% the number of defined blocks -\setcounter{ALG@blocknr}{0} -\newcounter{ALG@storecount}% number of stored but not restored algorithmic environments -\setcounter{ALG@storecount}{0} -\newcounter{ALG@tmpcounter}% only to decrement things -\newlength\ALG@tmplength% -%\def\algorithmicnoindent{-\ALG@tlm} -% \def\algbackskipbegin{\hskip\ALG@ctlm} -%\def\algbackskip{\hskip-\ALG@thistlm} -%\def\algbackskipend{\hskip-\ALG@tlm} -\def\ALG@defaultindent{\algorithmicindent} -% -% conditional states -% -\def\ALG@newcondstate#1% - {% - \expandafter\edef\csname ALG@x@#1\endcsname% - {\expandafter\noexpand\csname @@ALG@x@#1\endcsname}% - }% -\ALG@newcondstate{notext}% -\ALG@newcondstate{default}% -% -% -% *** ALGORITHMIC *** -% -% -\newcommand\ALG@beginblock[1]% #1 - indentation - {% - \ALG@thistlm\ALG@tlm% - \addtolength\ALG@tlm{#1}% - \addtocounter{ALG@nested}{1}% - \setlength\ALG@tmplength{#1}% - \expandafter\edef\csname ALG@ind@\theALG@nested\endcsname{\the\ALG@tmplength}% - }% -\newcommand\ALG@endblock% - {% - \addtolength\ALG@tlm{-\csname ALG@ind@\theALG@nested\endcsname}% - \addtocounter{ALG@nested}{-1}% - \ALG@thistlm\ALG@tlm% - }% -% -% algorithmic environment -% -\def\ALG@step% - {% - \addtocounter{ALG@line}{1}% - \addtocounter{ALG@rem}{1}% - \ifthenelse{\equal{\arabic{ALG@rem}}{\ALG@numberfreq}}% - {\setcounter{ALG@rem}{0}\alglinenumber{\arabic{ALG@line}}}% - {}% - }% -\newenvironment{algorithmic}[1][0]% - {% - \edef\ALG@numberfreq{#1}% - \def\@currentlabel{\theALG@line}% - % - \setcounter{ALG@line}{0}% - \setcounter{ALG@rem}{0}% - % - \let\\\algbreak% - % - \expandafter\edef\csname ALG@currentblock@\theALG@nested\endcsname{0}% - \expandafter\let\csname ALG@currentlifetime@\theALG@nested\endcsname\relax% - % - \begin{list}% - {\ALG@step}% - {% - \rightmargin\z@% - \itemsep\z@ \itemindent\z@ \listparindent2em% - \partopsep\z@ \parskip\z@ \parsep\z@% - \labelsep 0.5em \topsep 0.2em%\skip 1.2em - \ifthenelse{\equal{#1}{0}}% - {\labelwidth 0.5em}% - {\labelwidth 1.2em}% - \leftmargin\labelwidth \addtolength{\leftmargin}{\labelsep}% Ok. the perfect leftmargin :-)) - \ALG@tlm\z@% - }% - \setcounter{ALG@nested}{0}% - \ALG@beginalgorithmic% - }% - {% end{algorithmic} - % check if all blocks are closed - \ALG@closeloops% - \expandafter\ifnum\csname ALG@currentblock@\theALG@nested\endcsname=0\relax% - \else% - \PackageError{algorithmicx}{Some blocks are not closed!!!}{}% - \fi% - \ALG@endalgorithmic% - \end{list}% - }% -% -% -% *** Functional core *** -% -% -\def\ALG@makeentity#1% execute the entity (#1) - {% - \def\ALG@thisentity{#1}% - \expandafter\ifx\csname ALG@b@\ALG@L @#1@0\endcsname\relax% - \let\ALG@makenobeginrepeat\ALG@makenobegin\ALG@makenobeginrepeat% this entitie ends or continues blocks - \else% - \let\ALG@makebeginrepeat\ALG@makebegin\ALG@makebeginrepeat% this entitie can open blocks - \fi% - \ALG@entitiecommand% - }% -% -\def\ALG@makebegin% executes an entitie that can open blocks - {% - \expandafter\let\expandafter\ALG@thislifetime\csname ALG@currentlifetime@\theALG@nested\endcsname% - \ifx\ALG@thislifetime\relax% - \let\ALG@makebeginrepeat\ALG@doentity% in infinite block I can open my block - \else% - \ifnum\ALG@thislifetime>0\relax% - \ifnum\ALG@thislifetime>65534\else% - \setcounter{ALG@tmpcounter}{\ALG@thislifetime}% the block has 'space' for another included block - \addtocounter{ALG@tmpcounter}{-1}% - \expandafter\edef\csname ALG@currentlifetime@\theALG@nested\endcsname{\arabic{ALG@tmpcounter}}% - \fi% - \let\ALG@makebeginrepeat\ALG@doentity% - \else% the block needs to be closed - \expandafter\ifx\csname ALG@b@\ALG@L @\ALG@thisentity @\csname ALG@currentblock@\theALG@nested\endcsname\endcsname\relax% - \ALG@closebyforce% I can not close this block, continue after it is closed by force -% \ALG@makebegin% - \else% - % the block would be closed automatically, but this entitie can close it, so let's do it with the entity - \let\ALG@makebeginrepeat\ALG@doentity% - \fi% - \fi% - \fi% - \ALG@makebeginrepeat% - }% -% -\def\ALG@makenobegin% executes an entitie that can not open blocks - {% - \expandafter\ifx\csname ALG@currentlifetime@\theALG@nested\endcsname\relax% - \let\ALG@makenobeginrepeat\ALG@doentity% an infinite block must be broken - \else% - \expandafter\ifx\csname ALG@b@\ALG@L @\ALG@thisentity @\csname ALG@currentblock@\theALG@nested\endcsname\endcsname\relax% - \ALG@closebyforce% the block must be ended by force, - \else% - \let\ALG@makenobeginrepeat\ALG@doentity% I can continue / end this block, let's do it - \fi% - \fi% - \ALG@makenobeginrepeat% - }% -% -\def\ALG@dobegin% - {% - \ALG@beginblock{\csname ALG@i@\ALG@L @\ALG@thisentity @\ALG@thisblock\endcsname}% - \expandafter\edef\csname ALG@currentblock@\theALG@nested\endcsname{\csname ALG@b@\ALG@L @\ALG@thisentity @\ALG@thisblock\endcsname}% - \expandafter\ifx\csname ALG@c@\ALG@L @\ALG@thisentity @\ALG@thisblock\endcsname\relax% - \expandafter\let\csname ALG@currentlifetime@\theALG@nested\endcsname\relax% - \else% - \expandafter\edef\csname ALG@currentlifetime@\theALG@nested\endcsname{\csname ALG@c@\ALG@L @\ALG@thisentity @\ALG@thisblock\endcsname}% - \fi% - }% -% -\def\ALG@doend% - {% - \ALG@endblock% - }% -% -\def\ALG@doentity% the number of the closed block, the entitie - {% - \edef\ALG@thisblock{\csname ALG@currentblock@\theALG@nested\endcsname}% - \expandafter\ifx\csname ALG@b@\ALG@L @\ALG@thisentity @\ALG@thisblock\endcsname\relax% - \def\ALG@thisblock{0}% - \fi% - \ALG@getentitytext% - \ifnum\ALG@thisblock=0\else\ALG@doend\fi% - \ifx\ALG@text\ALG@x@notext% - \item[]\nointerlineskip%\vskip-\prevdepth\nointerlineskip% bug: if there are no text and no lines, then this is wrong - \else% - \item% - \fi% - \noindent\hskip\ALG@tlm% - \expandafter\ifnum0=\csname ALG@b@\ALG@L @\ALG@thisentity @\ALG@thisblock\endcsname\else% - \ALG@dobegin% - \fi% - \def\ALG@entitiecommand{\ALG@displayentity}% - }% -% -\def\ALG@getentitytext% - {% - \expandafter\let\expandafter\ALG@text\csname ALG@t@\ALG@L @\ALG@thisentity @\ALG@thisblock\endcsname% - \ifx\ALG@text\ALG@x@default% - % block specific - default - \expandafter\let\expandafter\ALG@text\csname ALG@t@\ALG@L @\ALG@thisentity\endcsname% - \ifx\ALG@text\ALG@x@default% - % block specific - default, language specific - default - \def\ALG@text{\ALG@deftext{\ALG@thisentity}}% - \fi% - \fi% - }% -% -\def\ALG@deftext{\csname ALG@deftext@\ALG@L\endcsname}% -% -\def\ALG@displayentity% - {% - \ifx\ALG@text\ALG@x@notext% - \let\ALG@text\relax% - \fi - \ALG@text% - }% -% -\def\ALG@closebyforce% - {% - \ALG@endblock% - }% -% -\def\ALG@closeloops% closes all finite blocks - {% - \expandafter\ifx\csname ALG@currentlifetime@\theALG@nested\endcsname\relax% - \else% only if it is finite - \ALG@closebyforce% the block must be ended by force, - \ALG@closeloops% the command still runs - \fi% - }% -% -% -% *** Low level block/entitie defining commands *** -% -% -\def\ALG@bl@{0}% the BIG block -\let\ALG@bl@@\ALG@bl@% the BIG block -% -% Create a block -% -\def\ALG@createblock#1% create the block #1, if it does not exists - {% - \@ifundefined{ALG@bl@\ALG@Ld @#1}% needs to be created? - {% - \addtocounter{ALG@blocknr}{1}% increment the block counter - \expandafter\edef\csname ALG@bl@\ALG@Ld @#1\endcsname{\arabic{ALG@blocknr}}% set the block number - }% - {}% - }% -% -% Get the block number -% -\def\ALG@getblocknumber#1{\csname ALG@bl@\ALG@Ld @#1\endcsname}% -% -% Create an entitie -% -\def\ALG@createentitie#1% create the entitie #1, if it does not exists - {% - \expandafter\ALG@edefcmd\csname #1\endcsname{\noexpand\ALG@makeentity{#1}}% - \@ifundefined{ALG@t@\ALG@Ld @#1}% the entity text is defined in this language? - {% - \expandafter\let\csname ALG@t@\ALG@Ld @#1\endcsname\ALG@x@default% - }% - {}% - }% -% -\def\ALG@createtext#1#2% #1 = closed block; #2 = entitie; creates \ALG@t@#2@#1 - {% - \expandafter\let\csname ALG@t@\ALG@Ld @#2@#1\endcsname\ALG@x@default% - }% -% -% End and Continue block -% -\def\ALG@endandcontinueblock#1#2#3#4#5% #1 = new block; #2 = old block; #3 = entitie; #4 = credits; #5 = indent - {% - \ifthenelse{\equal{#3}{}}{}% execute only if the entity is not empty - {% - \ALG@createentitie{#3}% create the entitie - \ALG@createblock{#2}% create the old block, if needed - \ifthenelse{\equal{#1}{}}% whe need to open a new block? - {\expandafter\edef\csname ALG@b@\ALG@Ld @#3@\ALG@getblocknumber{#2}\endcsname{0}}% no, just close the old one - {% yes, - \ALG@createblock{#1}% create the block - \expandafter\edef\csname ALG@b@\ALG@Ld @#3@\ALG@getblocknumber{#2}\endcsname{\ALG@getblocknumber{#1}}% ending the old block opens a new one - \ifthenelse{\equal{#4}{}}% infinite or finite credits? - {\expandafter\let\csname ALG@c@\ALG@Ld @#3@\ALG@getblocknumber{#2}\endcsname\relax}% infinite credits - {\expandafter\edef\csname ALG@c@\ALG@Ld @#3@\ALG@getblocknumber{#2}\endcsname{#4}}% finite credits - \ifthenelse{\equal{#5}{}}% default or specified indentation - {\expandafter\let\csname ALG@i@\ALG@Ld @#3@\ALG@getblocknumber{#2}\endcsname\ALG@defaultindent}% default indentation - {\expandafter\edef\csname ALG@i@\ALG@Ld @#3@\ALG@getblocknumber{#2}\endcsname{#5}}% indentation is specified - }% - \ALG@createtext{\ALG@getblocknumber{#2}}{#3}% - }% - }% -% -% macros used in declarations -% -\def\ALG@p@endtext@E{\algrenewtext{\ALG@v@end}}% -\def\ALG@p@endtext@xE{\algrenewtext[\ALG@v@newblock]{\ALG@v@end}}% -\def\ALG@p@endtext@nE{\algnotext{\ALG@v@end}}% -\def\ALG@p@endtext@xnE{\algnotext[\ALG@v@newblock]{\ALG@v@end}}% -\def\ALG@p@endtext@{}% -% starttext defines are more compex -- care must be taken for the optional parameters -\def\ALG@p@starttext@S{\ALG@p@s@process{\algrenewtext}}% -\def\ALG@p@starttext@C{\ALG@p@s@process{\algrenewtext}}% -\def\ALG@p@starttext@xC{\ALG@p@s@process{\algrenewtext[\ALG@v@oldblock]}}% -\def\ALG@p@s@process#1% - {% - \ifthenelse{\equal{\ALG@v@start}{}}% - {\ALG@p@endtext}% - {\@ifnextchar{[}{\ALG@p@s@getparamcount{#1}}{\ALG@p@s@simple{#1}}}% - }% -\def\ALG@p@s@getparamcount#1[#2]% - {% - \@ifnextchar{[}{\ALG@p@s@getdefparam{#1}{#2}}{\ALG@p@s@param{#1}{#2}}% - }% -\def\ALG@p@s@getdefparam#1#2[#3]% - {% - \ALG@p@s@defparam{#1}{#2}{#3}% - }% -\def\ALG@p@s@simple#1#2{#1{\ALG@v@start}{#2}\ALG@p@endtext}% -\def\ALG@p@s@param#1#2#3{#1{\ALG@v@start}[#2]{#3}\ALG@p@endtext}% -\def\ALG@p@s@defparam#1#2#3#4{#1{\ALG@v@start}[#2][#3]{#4}\ALG@p@endtext}% -% the rest of the crew -\def\ALG@p@starttext@nS{\algnotext{\ALG@v@start}\ALG@p@endtext}% -\def\ALG@p@starttext@nC{\algnotext{\ALG@v@start}\ALG@p@endtext}% -\def\ALG@p@starttext@xnC{\algnotext[\ALG@v@oldblock]{\ALG@v@start}\ALG@p@endtext}% -\def\ALG@p@starttext@{\ALG@p@endtext}% -\def\ALG@p@indent@def#1{\def\ALG@v@indent{#1}\ALG@p@setup}% -\def\ALG@p@indent@{\def\ALG@v@indent{}\ALG@p@setup}% -\def\ALG@p@credits@def#1{\def\ALG@v@credits{#1}\ALG@p@indent}% -\def\ALG@p@credits@{\ALG@p@indent}% -\def\ALG@p@end@def#1{\def\ALG@v@end{#1}\ALG@p@credits}% -\def\ALG@p@end@{\def\ALG@v@end{}\ALG@p@credits}% -\def\ALG@p@start@def#1{\def\ALG@v@start{#1}\ALG@p@end}% -\def\ALG@p@start@{\def\ALG@v@start{}\ALG@p@end}% -\def\ALG@p@oldblock@def#1{\def\ALG@v@oldblock{#1}\ALG@p@start}% -\def\ALG@p@oldblock@{\def\ALG@v@oldblock{}\ALG@p@start}% -\newcommand\ALG@p@newblock[1][]{\def\ALG@v@newblock{#1}\ALG@p@oldblock}% -\def\ALG@p@setup% - {% - \ifthenelse{\equal{\ALG@v@newblock}{}}% - {% - \ifthenelse{\equal{\ALG@v@start}{}}% - {% - \PackageError{algorithmicx}{Block or starting entitie must be specified!!!}{}% - }% - {% - \let\ALG@v@newblock\ALG@v@start% - }% - }% - {% - }% - \ALG@endandcontinueblock% - {\ALG@v@newblock}{\ALG@v@oldblock}{\ALG@v@start}% - {\ALG@v@credits}{\ALG@v@indent}% - \ALG@endandcontinueblock% - {}{\ALG@v@newblock}{\ALG@v@end}% - {}{}% - \ALG@p@starttext% - }% -% -% param handling -% -\newcommand\ALG@p@def[2][def]% - {% - \expandafter\let\csname ALG@p@#2\expandafter\endcsname\csname ALG@p@#2@#1\endcsname% - }% -\def\ALG@p@undef{\ALG@p@def[]}% -% -\def\ALG@p@ons{\ALG@p@def{start}}% -\def\ALG@p@onS{\ALG@p@def{start}\ALG@p@def[S]{starttext}}% -\def\ALG@p@onc{\ALG@p@def{oldblock}\ALG@p@def{start}}% -\def\ALG@p@onC{\ALG@p@def{oldblock}\ALG@p@def{start}\ALG@p@def[C]{starttext}}% -\def\ALG@p@one{\ALG@p@def{end}}% -\def\ALG@p@onE{\ALG@p@def{end}\ALG@p@def[E]{endtext}}% -\def\ALG@p@onxC{\ALG@p@def{oldblock}\ALG@p@def{start}\ALG@p@def[xC]{starttext}}% -\def\ALG@p@onxE{\ALG@p@def{end}\ALG@p@def[xE]{endtext}}% -\def\ALG@p@onnS{\ALG@p@def{start}\ALG@p@def[nS]{starttext}}% -\def\ALG@p@onnC{\ALG@p@def{oldblock}\ALG@p@def{start}\ALG@p@def[nC]{starttext}}% -\def\ALG@p@onnE{\ALG@p@def{end}\ALG@p@def[nE]{endtext}}% -\def\ALG@p@onxnC{\ALG@p@def{oldblock}\ALG@p@def{start}\ALG@p@def[xnC]{starttext}}% -\def\ALG@p@onxnE{\ALG@p@def{end}\ALG@p@def[xnE]{endtext}}% -\def\ALG@p@onb{\def\ALG@v@credits{}}% -\def\ALG@p@onl{\def\ALG@v@credits{1}}% -\def\ALG@p@onL{\ALG@p@def{credits}}% -\def\ALG@p@oni{\ALG@p@def{indent}}% -% -\def\ALG@p@main#1% - {% - \@ifundefined{ALG@ps@\ALG@p@state @#1}% - {% - \csname ALG@ps@\ALG@p@state @other\endcsname{#1}% - }% - {% - \csname ALG@ps@\ALG@p@state @#1\endcsname% - }% - \ALG@p@rec% - }% -% STATE : <> -\expandafter\def\csname ALG@ps@@]\endcsname{\let\ALG@p@rec\relax}% -\def\ALG@ps@@s{\ALG@p@ons}% -\def\ALG@ps@@S{\ALG@p@onS}% -\def\ALG@ps@@c{\ALG@p@onc}% -\def\ALG@ps@@C{\ALG@p@onC}% -\def\ALG@ps@@e{\ALG@p@one}% -\def\ALG@ps@@E{\ALG@p@onE}% -\def\ALG@ps@@N{\typeout{algdef: 'N' obsoloted, use 'nE'.}\ALG@p@onnE}% -\def\ALG@ps@@b{\ALG@p@onb}% -\def\ALG@ps@@l{\ALG@p@onl}% -\def\ALG@ps@@L{\ALG@p@onL}% -\def\ALG@ps@@i{\ALG@p@oni}% -\def\ALG@ps@@x{\def\ALG@p@state{x}}% -\def\ALG@ps@@n{\def\ALG@p@state{n}}% -\def\ALG@ps@@other#1{\typeout{algdef: Ignoring unknown token #1}}% -% STATE : x -\def\ALG@ps@x@C{\def\ALG@p@state{}\ALG@p@onxC}% -\def\ALG@ps@x@E{\def\ALG@p@state{}\ALG@p@onxE}% -\def\ALG@ps@x@N{\def\ALG@p@state{}\typeout{algdef: 'xN' obsoloted, use 'xnE'.}\ALG@p@onxnE}% -\def\ALG@ps@x@n{\def\ALG@p@state{xn}}% -\def\ALG@ps@x@other#1% - {% - \typeout{algdef: Ignoring 'x' before '#1'.}% - \def\ALG@p@state{}% - \def\ALG@p@rec{\let\ALG@p@rec\ALG@p@main\ALG@p@rec#1}% - }% -% STATE : n -\def\ALG@ps@n@S{\def\ALG@p@state{}\ALG@p@onnS}% -\def\ALG@ps@n@C{\def\ALG@p@state{}\ALG@p@onnC}% -\def\ALG@ps@n@E{\def\ALG@p@state{}\ALG@p@onnE}% -\def\ALG@ps@n@x{\def\ALG@p@state{nx}}% -\def\ALG@ps@n@other#1% - {% - \typeout{algdef: Ignoring 'n' before '#1'.}% - \def\ALG@p@state{}% - \def\ALG@p@rec{\let\ALG@p@rec\ALG@p@main\ALG@p@rec#1}% - }% -% STATE : xn -\def\ALG@ps@xn@C{\def\ALG@p@state{}\ALG@p@onxnC}% -\def\ALG@ps@xn@E{\def\ALG@p@state{}\ALG@p@onxnE}% -\def\ALG@ps@xn@x{\typeout{algdef: Ignoring 'x' after 'xn'.}}% -\def\ALG@ps@xn@n{\typeout{algdef: Ignoring 'n' after 'xn'.}}% -\def\ALG@ps@xn@other#1% - {% - \typeout{algdef: Ignoring 'xn' before '#1'.}% - \def\ALG@p@state{}% - \def\ALG@p@rec{\let\ALG@p@rec\ALG@p@main\ALG@p@rec#1}% - }% -% STATE : nx -\def\ALG@ps@nx@C{\def\ALG@p@state{}\ALG@p@onxnC}% -\def\ALG@ps@nx@E{\def\ALG@p@state{}\ALG@p@onxnE}% -\def\ALG@ps@nx@x{\typeout{algdef: Ignoring 'x' after 'nx'.}}% -\def\ALG@ps@nx@n{\typeout{algdef: Ignoring 'n' after 'nx'.}}% -\def\ALG@ps@nx@other#1% - {% - \typeout{algdef: Ignoring 'nx' before '#1'.}% - \def\ALG@p@state{}% - \def\ALG@p@rec{\let\ALG@p@rec\ALG@p@main\ALG@p@rec#1}% - }% -% -% -% *** User level block/entitie commands *** -% -% -% -% algdef{switches}... -- the king of all definitions in the algorithmicx package -% -\newcommand\algdef[1]% - {% - \ALG@p@undef{oldblock}% - \ALG@p@undef{start}% - \ALG@p@undef{end}% - \def\ALG@v@credits{}% - \ALG@p@undef{credits}% - \ALG@p@undef{indent}% - \ALG@p@undef{starttext}% - \ALG@p@undef{endtext}% - \def\ALG@p@state{}% - \let\ALG@p@rec\ALG@p@main% - \ALG@p@rec#1]% - \ALG@p@newblock% - }% -% -% a lot of other macros are provided for convenience -% -\def\algblock{\algdef{se}}% -\def\algcblock{\algdef{ce}}% -\def\algloop{\algdef{sl}}% -\def\algcloop{\algdef{cl}}% -\def\algsetblock{\algdef{seLi}}% -\def\algsetcblock{\algdef{ceLi}}% -\def\algblockx{\algdef{SxE}}% -\def\algblockdefx{\algdef{SE}}% -\def\algcblockx{\algdef{CxE}}% -\def\algcblockdefx{\algdef{CE}}% -\def\algsetblockx{\algdef{SxELi}}% -\def\algsetblockdefx{\algdef{SELi}}% -\def\algsetcblockx{\algdef{CxELi}}% -\def\algsetcblockdefx{\algdef{CELi}}% -\def\algloopdefx{\algdef{Sl}}% -\def\algcloopx{\algdef{xCl}}% -\def\algcloopdefx{\algdef{Cl}}% -% algloopx is not correct, use algloopdefx -% -% Text output commands -% -\newcommand\algrenewtext[2][]% [block]{entity} - {% - \ifthenelse{\equal{#2}{}}{}% - {% - \ifthenelse{\equal{#1}{}}% - {% - \expandafter\let\csname ALG@t@\ALG@Ld @#2\endcsname\relax% - \expandafter\newcommand\csname ALG@t@\ALG@Ld @#2\endcsname% - }% - {% - \expandafter\let\csname ALG@t@\ALG@Ld @#2@\ALG@getblocknumber{#1}\endcsname\relax% - \expandafter\newcommand\csname ALG@t@\ALG@Ld @#2@\ALG@getblocknumber{#1}\endcsname% - }% - }% - }% -% -\def\ALG@letentitytext#1#2% [block]{entity} - {% - \ifthenelse{\equal{#2}{}}{}% - {% - \ifthenelse{\equal{#1}{}}% - {% - \expandafter\let\csname ALG@t@\ALG@Ld @#2\endcsname% - }% - {% - \expandafter\let\csname ALG@t@\ALG@Ld @#2@\ALG@getblocknumber{#1}\endcsname% - }% - }% - }% -% -\newcommand\algnotext[2][]% [block]{entity} - {% - \ALG@letentitytext{#1}{#2}\ALG@x@notext% - }% -% -\newcommand\algdefaulttext[2][]% [block]{entity} - {% - \ALG@letentitytext{#1}{#2}\ALG@x@default% - }% -% -\def\ALG@notext*{\algnotext}% -\def\algtext{\@ifnextchar{*}{\ALG@notext}{\algrenewtext}}% -% -% -% *** LANGUAGE SWITCHING *** -% -% -% -\newcommand\algnewlanguage[1]% - {% - \@ifundefined{ALG@L@#1}% needs to be created? - {}% - {% - \PackageError{algorithmicx}{Language '#1' already defined!}{}% - }% - \addtocounter{ALG@Lnr}{1}% increment the language counter - \expandafter\edef\csname ALG@L@#1\endcsname{\arabic{ALG@Lnr}}% set the language number - \edef\ALG@Ld{\csname ALG@L@#1\endcsname}% - \expandafter\let\csname ALG@bl@\ALG@Ld @\endcsname\ALG@bl@% the BIG block - \expandafter\let\csname ALG@bl@\ALG@Ld @@\endcsname\ALG@bl@% the BIG block - \algdef{SL}[STATE]{State}{0}{}% - \expandafter\def\csname ALG@deftext@\ALG@Ld\endcsname{\textbf}% - \algnewcommand\algorithmiccomment[1]{\hfill\(\triangleright\) ##1}% - \algnewcommand\algorithmicindent{1.5em}% - \algnewcommand\alglinenumber[1]{\footnotesize ##1:}% - \algnewcommand\ALG@beginalgorithmic\relax% for user overrides - \algnewcommand\ALG@endalgorithmic\relax% for user overrides - }% -% -\newcommand\algsetlanguage[1]% - {% - \@ifundefined{ALG@L@#1}% needs to be created? - {% - \PackageError{algorithmicx}{Language '#1' is not yet defined!}{}% - }{}% - \edef\ALG@L{\csname ALG@L@#1\endcsname}% - }% -% -\newcommand\algdeflanguage[1]% - {% - \@ifundefined{ALG@L@#1}% needs to be created? - {% - \PackageError{algorithmicx}{Language '#1' is not yet defined!}{}% - }{}% - \edef\ALG@Ld{\csname ALG@L@#1\endcsname}% - }% -% -\newcommand\alglanguage[1]% - {% - \algdeflanguage{#1}% - \algsetlanguage{#1}% - }% -% -% -% *** Defining language dependent stuff *** -% -% -\def\ALG@eatoneparam#1{}% -\def\ALG@defbasecmd#1#2% - {% - \edef\ALG@tmp{\expandafter\ALG@eatoneparam\string #2}% - \@ifundefined\ALG@tmp{\edef #2{\noexpand\csname ALG@cmd@\noexpand\ALG@L @\ALG@tmp\endcsname}}{}% - \expandafter#1\csname ALG@cmd@\ALG@Ld @\ALG@tmp\endcsname% - }% -\newcommand\algnewcommand{\ALG@defbasecmd\newcommand}% -\newcommand\algrenewcommand{\ALG@defbasecmd\renewcommand}% -\def\ALG@letcmd{\ALG@defbasecmd\let}% -\def\ALG@defcmd{\ALG@defbasecmd\def}% -\def\ALG@edefcmd{\ALG@defbasecmd\edef}% -% -% -% *** OTHERS *** -% -% -\def\BState{\State \algbackskip}% -\def\Statex{\item[]}% an empty line -\newcommand\algrenewcomment{\algrenewcommand\algorithmiccomment}% -\def\Comment{\algorithmiccomment}% -\def\algref#1#2{\ref{#1}.\ref{#2}}% -\algnewlanguage{default}% -\algsetlanguage{default}% -% -% -% *** Line breaks *** -% -% -\newcommand\algbreak% for multiline parameters !!! needs fix - {% - \item% -% \hskip\ALG@parindent%!!! not yet implemented -% \hskip-\algorithmicindent% - }% -% -\def\ALG@noputindents% - {% - \hskip\ALG@tlm% - }% -% -% -% *** algorithm store / restore *** -% -% -% store -% -\ALG@newcondstate{mustrestore}% -\def\algstore% - {% - \renewcommand\ALG@beginblock% - {% - \PackageError{algorithmicx}{The environment must be closed after store!}{}% - }% - \@ifstar{\ALG@starstore}{\ALG@nostarstore}% - }% -\def\ALG@nostarstore#1% save all infos into #1 and terminate the algorithmic block - {% - \addtocounter{ALG@storecount}{1}% - \expandafter\global\expandafter\let\csname ALG@save@mustrestore@#1\endcsname\ALG@x@mustrestore% - \ALG@starstore{#1}% - }% -\def\ALG@starstore#1% - {% - \@ifundefined{ALG@save@line@#1}{}% - {\PackageError{algorithmicx}{This save name '#1' is already used!}{}}% - \def\ALG@savename{#1}% - \expandafter\xdef\csname ALG@save@totalnr@\ALG@savename\endcsname{\theALG@nested}% - \expandafter\xdef\csname ALG@save@line@\ALG@savename\endcsname{\theALG@line}% - \expandafter\xdef\csname ALG@save@numberfreq@\ALG@savename\endcsname{\ALG@numberfreq}% - \expandafter\xdef\csname ALG@save@rem@\ALG@savename\endcsname{\theALG@rem}% - \let\ALG@storerepeat\ALG@store% - \ALG@storerepeat% - }% -\def\ALG@store% simply terminate all open blocks - {% - \ifnum\theALG@nested=0\let\ALG@storerepeat\relax% - \else% - \expandafter\xdef\csname ALG@save@currentblock@\ALG@savename @\theALG@nested\endcsname% - {\csname ALG@currentblock@\theALG@nested\endcsname}% - \expandafter\ifx\csname ALG@currentlifetime@\theALG@nested\endcsname\relax% - \else% - \expandafter\xdef\csname ALG@save@currentlifetime@\ALG@savename @\theALG@nested\endcsname% - {\csname ALG@currentlifetime@\theALG@nested\endcsname}% - \fi% - \expandafter\xdef\csname ALG@save@ind@\ALG@savename @\theALG@nested\endcsname% - {\csname ALG@ind@\theALG@nested\endcsname}% - \ALG@closebyforce% - \fi% - \ALG@storerepeat% - }% -% -% restore -% -\def\algrestore% - {% - \@ifstar{\ALG@starrestore}{\ALG@nostarrestore}% - }% -\def\ALG@starrestore% - {% - \let\ALG@restorerem\relax% - \let\ALG@restorereprem\relax% - \ALG@restoremain% - }% -\def\ALG@nostarrestore% - {% - \let\ALG@restorerem\ALG@restoreremovesave% - \let\ALG@restorereprem\ALG@restorerepremovesave% - \ALG@restoremain% - }% -\def\ALG@restoreremovesave% - {% - \expandafter\global\expandafter\let\csname ALG@save@totalnr@\ALG@savename\endcsname\relax% - \expandafter\global\expandafter\let\csname ALG@save@line@\ALG@savename\endcsname\relax% - \expandafter\global\expandafter\let\csname ALG@save@rem@\ALG@savename\endcsname\relax% - \expandafter\global\expandafter\let\csname ALG@save@totalnr@\ALG@savename\endcsname\relax% - \expandafter\global\expandafter\let\csname ALG@save@numberfreq@\ALG@savename\endcsname\relax% - }% -\def\ALG@restorerepremovesave% - {% - \expandafter\global\expandafter\let\csname ALG@save@currentblock@\ALG@savename @\theALG@tmpcounter\endcsname\relax% - \expandafter\global\expandafter\let\csname ALG@save@currentlifetime@\ALG@savename @\theALG@tmpcounter\endcsname\relax% - \expandafter\global\expandafter\let\csname ALG@save@currentlifetime@\ALG@savename @\theALG@tmpcounter\endcsname\relax% - \expandafter\global\expandafter\let\csname ALG@save@ind@\ALG@savename @\theALG@tmpcounter\endcsname\relax% - }% -\def\ALG@restoremain#1% restore all infos from #1 in an open algorithmic block - {% - \ifnum\theALG@line=0% - \else\PackageError{algorithmicx}{Restore might be used only at the beginning of the environment!}{}% - \fi% - \def\ALG@savename{#1}% - \expandafter\ifx\csname ALG@save@totalnr@\ALG@savename\endcsname\relax% - \PackageError{algorithmicx}{Save '\ALG@savename'\space not defined!!!}{}% - \fi% - \@ifundefined{ALG@save@mustrestore@\ALG@savename}{}% - {% - \addtocounter{ALG@storecount}{-1}% - \expandafter\global\expandafter\let\csname ALG@save@mustrestore@\ALG@savename\endcsname\relax% - }% - \setcounter{ALG@line}{\csname ALG@save@line@\ALG@savename\endcsname}% - \edef\ALG@numberfreq{\csname ALG@save@numberfreq@\ALG@savename\endcsname}% - \setcounter{ALG@rem}{\csname ALG@save@rem@\ALG@savename\endcsname}% - \setcounter{ALG@tmpcounter}{\csname ALG@save@totalnr@\ALG@savename\endcsname}% - \setcounter{ALG@nested}{0}% - \ALG@restorerem% - \let\ALG@restorerepeat\ALG@restore% - \ALG@restorerepeat% - }% -\def\ALG@restore% - {% - \ifnum\theALG@tmpcounter>0% - \expandafter\edef\csname ALG@currentblock@\theALG@tmpcounter\endcsname% - {\csname ALG@save@currentblock@\ALG@savename @\theALG@tmpcounter\endcsname}% - \expandafter\ifx\csname ALG@save@currentlifetime@\ALG@savename @\theALG@tmpcounter\endcsname\relax% - \expandafter\let\csname ALG@currentlifetime@\theALG@tmpcounter\endcsname\relax% - \else% - \expandafter\edef\csname ALG@currentlifetime@\theALG@tmpcounter\endcsname% - {\csname ALG@save@currentlifetime@\ALG@savename @\theALG@tmpcounter\endcsname}% - \fi% - % - \ALG@beginblock{\csname ALG@save@ind@\ALG@savename @\theALG@tmpcounter\endcsname}% - \ALG@restorereprem% - \addtocounter{ALG@tmpcounter}{-1}% - \else\let\ALG@restorerepeat\relax% - \fi% - \ALG@restorerepeat% - }% -\AtEndDocument% - {% - \ifnum\theALG@storecount>0\relax% - \PackageError{algorithmicx}{Some stored algorithms are not restored!}{}% - \fi% - }% diff --git a/report/pyp_clustering/acl09-short/common/algpseudocode.sty b/report/pyp_clustering/acl09-short/common/algpseudocode.sty deleted file mode 100644 index fca966ac..00000000 --- a/report/pyp_clustering/acl09-short/common/algpseudocode.sty +++ /dev/null @@ -1,92 +0,0 @@ -% PSEUDOCODE ALGORITHMIC STYLE -- Released 27 APR 2005 -% for LaTeX version 2e -% -% Copyright Szasz Janos -% E-mail szaszjanos@users.sourceforge.net -% Based on Peter Williams's algorithmic.sty -% -\NeedsTeXFormat{LaTeX2e}% -\ProvidesPackage{algpseudocode}% -\RequirePackage{ifthen}% -\RequirePackage{algorithmicx}% -\typeout{Document Style - pseudocode environments for use with the `algorithmicx' style}% -% -\def\ALG@noend{f}% -\newboolean{ALG@compatible}% -\setboolean{ALG@compatible}{false}% -% -\DeclareOption{noend}{\def\ALG@noend{t}}% -\DeclareOption{end}{\def\ALG@noend{f}}% -\DeclareOption{compatible}{\typeout{For compatibility mode use algcompatible.sty!!!}\setboolean{ALG@compatible}{true}}% -\DeclareOption{noncompatible}{\setboolean{ALG@noncompatible}{false}}% -\ProcessOptions% -% -% *** DECLARATIONS *** -% -\algnewlanguage{pseudocode}% -\alglanguage{pseudocode}% -% -% *** KEYWORDS *** -% -\algnewcommand\algorithmicend{\textbf{end}} -\algnewcommand\algorithmicdo{\textbf{do}} -\algnewcommand\algorithmicwhile{\textbf{while}} -\algnewcommand\algorithmicfor{\textbf{for}} -\algnewcommand\algorithmicforall{\textbf{for all}} -\algnewcommand\algorithmicloop{\textbf{loop}} -\algnewcommand\algorithmicrepeat{\textbf{repeat}} -\algnewcommand\algorithmicuntil{\textbf{until}} -\algnewcommand\algorithmicprocedure{\textbf{procedure}} -\algnewcommand\algorithmicfunction{\textbf{function}} -\algnewcommand\algorithmicif{\textbf{if}} -\algnewcommand\algorithmicthen{\textbf{then}} -\algnewcommand\algorithmicelse{\textbf{else}} -\algnewcommand\algorithmicrequire{\textbf{Require:}} -\algnewcommand\algorithmicensure{\textbf{Ensure:}} -\algnewcommand\algorithmicreturn{\textbf{return}} -\algnewcommand\textproc{\textsc} -% -% *** DECLARED LOOPS *** -% -\algdef{SE}[WHILE]{While}{EndWhile}[1]{\algorithmicwhile\ #1\ \algorithmicdo}{\algorithmicend\ \algorithmicwhile}% -\algdef{SE}[FOR]{For}{EndFor}[1]{\algorithmicfor\ #1\ \algorithmicdo}{\algorithmicend\ \algorithmicfor}% -\algdef{S}[FOR]{ForAll}[1]{\algorithmicforall\ #1\ \algorithmicdo}% -\algdef{SE}[LOOP]{Loop}{EndLoop}{\algorithmicloop}{\algorithmicend\ \algorithmicloop}% -\algdef{SE}[REPEAT]{Repeat}{Until}{\algorithmicrepeat}[1]{\algorithmicuntil\ #1}% -\algdef{SE}[IF]{If}{EndIf}[1]{\algorithmicif\ #1\ \algorithmicthen}{\algorithmicend\ \algorithmicif}% -\algdef{C}[IF]{IF}{ElsIf}[1]{\algorithmicelse\ \algorithmicif\ #1\ \algorithmicthen}% -\algdef{Ce}[ELSE]{IF}{Else}{EndIf}{\algorithmicelse}% -\algdef{SE}[PROCEDURE]{Procedure}{EndProcedure}% - [2]{\algorithmicprocedure\ \textproc{#1}\ifthenelse{\equal{#2}{}}{}{(#2)}}% - {\algorithmicend\ \algorithmicprocedure}% -\algdef{SE}[FUNCTION]{Function}{EndFunction}% - [2]{\algorithmicfunction\ \textproc{#1}\ifthenelse{\equal{#2}{}}{}{(#2)}}% - {\algorithmicend\ \algorithmicfunction}% -% -\ifthenelse{\equal{\ALG@noend}{t}}% - {% - \algtext*{EndWhile}% - \algtext*{EndFor}% - \algtext*{EndLoop}% - \algtext*{EndIf}% - \algtext*{EndProcedure}% - \algtext*{EndFunction}% - }{}% -% -% *** OTHER DECLARATIONS *** -% -\algnewcommand\Require{\item[\algorithmicrequire]}% -\algnewcommand\Ensure{\item[\algorithmicensure]}% -\algnewcommand\Return{\algorithmicreturn{} }% -\algnewcommand\Call[2]{\textproc{#1}\ifthenelse{\equal{#2}{}}{}{(#2)}}% -% -% -% -\ifthenelse{\boolean{ALG@compatible}}% - {% - \ifthenelse{\equal{\ALG@noend}{t}}% - {\RequirePackage[noend]{algcompatible}}% - {\RequirePackage{algcompatible}}% - }% - {}% -% diff --git a/report/pyp_clustering/acl09-short/common/brief.bib b/report/pyp_clustering/acl09-short/common/brief.bib deleted file mode 100644 index d6fce84b..00000000 --- a/report/pyp_clustering/acl09-short/common/brief.bib +++ /dev/null @@ -1,2842 +0,0 @@ -%% This BibTeX bibliography file was created using BibDesk. -%% http://bibdesk.sourceforge.net/ - - -%% Created for Phil Blunsom at 2009-11-29 15:52:57 +0000 - - -%% Saved with string encoding Unicode (UTF-8) - - -@string{+aaai1980 = {Proc.\ of the 1st Conference on Artificial Intelligence (AAAI-80)}} - -@string{+aaai1991 = {Proc.\ of the 9th Annual Conference on Artificial Intelligence (AAAI-91)}} - -@string{+acl1983 = {Proc.\ of the 21st Annual Meeting of the ACL}} - -@string{+acl1984 = {Proc.\ of the 22nd Annual Meeting of the ACL}} - -@string{+acl1985 = {Proc.\ of the 23rd Annual Meeting of the ACL}} - -@string{+acl1986 = {Proc.\ of the 24th Annual Meeting of the ACL}} - -@string{+acl1987 = {Proc.\ of the 25th Annual Meeting of the ACL}} - -@string{+acl1988 = {Proc.\ of the 26th Annual Meeting of the ACL}} - -@string{+acl1989 = {Proc.\ of the 27th Annual Meeting of the ACL}} - -@string{+acl1990 = {Proc.\ of the 28th Annual Meeting of the ACL}} - -@string{+acl1991 = {Proc.\ of the 29th Annual Meeting of the ACL}} - -@string{+acl1992 = {Proc.\ of the 30th Annual Meeting of the ACL}} - -@string{+acl1992-ss = {Proc.\ of the 30th Annual Meeting of the ACL, Student Session}} - -@string{+acl1993 = {Proc.\ of the 31st Annual Meeting of the ACL}} - -@string{+acl1994 = {Proc.\ of the 32nd Annual Meeting of the ACL}} - -@string{+acl1995 = {Proc.\ of the 33rd Annual Meeting of the ACL}} - -@string{+acl1996 = {Proc.\ of the 34th Annual Meeting of the ACL}} - -@string{+acl1997 = {Proc.\ of the 35th Annual Meeting of the ACL and 8th Conference of the EACL (ACL-EACL'97)}} - -@string{+acl1997ws-ca = {Proc.\ of ACL/EACL'97 Workshop on Natural Language Processing for Communication Aids}} - -@string{+acl1997ws-ie = {Proc.\ of ACL/EACL'97 Workshop on Automatic Information Extraction and Building of Lexical Semantic Resources for NLP Applications}} - -@string{+acl1998 = {Proc.\ of the 36th Annual Meeting of the ACL and 17th International Conference on Computational Linguistics: COLING/ACL-98}} - -@string{+acl1998-ss = {Proc.\ of the 36th Annual Meeting of the ACL and 17th International Conference on Computational Linguistics (COLING/ACL-98), Student Session}} - -@string{+acl1999 = {Proc.\ of the 37th Annual Meeting of the ACL}} - -@string{+acl2000 = {Proc.\ of the 38th Annual Meeting of the ACL}} - -@string{+acl2001 = {Proc.\ of the 39th Annual Meeting of the ACL and 10th Conference of the EACL (ACL-EACL 2001)}} - -@string{+acl2001-ddmt = {Proc.\ of the ACL/EACL 2001 Workshop on Data-Driven Methods in Machine Translation}} - -@string{+acl2001-wscoll = {Proc.\ of the ACL/EACL 2001 Workshop on the Computational Extraction, Analysis and Exploitation of Collocations}} - -@string{+acl2002 = {Proc.\ of the 40th Annual Meeting of the ACL and 3rd Annual Meeting of the NAACL (ACL-2002)}} - -@string{+acl2002-lexacq = {Proc.\ of the ACL-2002 SIGLEX Workshop on Unsupervised Lexical Acquisition}} - -@string{+acl2002-sigphon = {Proc.\ of the 6th Meeting of the ACL Special Interest Group in Computational Phonology}} - -@string{+acl2002-ss = {Proc.\ of the Student Research Workshop, 40th Annual Meeting of the ACL (ACL-2002)}} - -@string{+acl2002-wsd = {Proc.\ of the ACL-2002 Workshop on Word Sense Disambiguation: Recent Successes and Future Directions}} - -@string{+acl2003 = {Proc.\ of the 41st Annual Meeting of the ACL (ACL-2003)}} - -@string{+acl2003-mwe = {Proc.\ of the ACL-2003 Workshop on Multiword Expressions: Analysis, Acquisition and Treatment}} - -@string{+acl2004 = {Proc.\ of the 42nd Annual Meeting of the ACL (ACL-2004)}} - -@string{+acl2004-mwe = {Proc.\ of the ACL 2004 Workshop on Multiword Expressions: Integrating Processing}} - -@string{+acl2004-senseval = {Proc.\ of Senseval-3: Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text}} - -@string{+acl2004-tmi = {Proc.\ of the 2nd Workshop on Text Meaning and Interpretation}} - -@string{+acl2005 = {Proc.\ of the 43rd Annual Meeting of the ACL (ACL-2005)}} - -@string{+acl2005-dla = {Proc.\ of the ACL 2005 Workshop on Deep Lexical Acquisition}} - -@string{+acl2005-pt = {Proc.\ of the ACL 2005 Workshop on Parallel Texts}} - -@string{+acl2006 = {Proc.\ of the 44th Annual Meeting of the ACL and 21st International Conference on Computational Linguistics (COLING/ACL-2006)}} - -@string{+acl2007 = {Proc.\ ACL}} - -@string{+acl2008 = {Proc.\ of the 46th Annual Conference of the Association for Computational Linguistics: Human Language Technologies (ACL-08:HLT)}} - -@string{+acl2009 = {Proc.\ ACL/IJCNLP-09}} - -@string{+amta1998 = {Proc.\ of AMTA'98: Conference of the Association for Machine Translation in the Americas}} - -@string{+amta2002 = {Proc.\ of the 6th Conference of the Association for Machine Translation in the Americas (AMTA)}} - -@string{+anlp1988 = {Proc.\ of the 2nd Conference on Applied Natural Language Processing (ANLP)}} - -@string{+anlp1992 = {Proc.\ of the 3rd Conference on Applied Natural Language Processing (ANLP)}} - -@string{+anlp1994 = {Proc.\ of the 4th Conference on Applied Natural Language Processing (ANLP)}} - -@string{+anlp1997 = {Proc.\ of the 5th Conference on Applied Natural Language Processing (ANLP)}} - -@string{+anlp2000 = {Proc.\ of the 6th Conference on Applied Natural Language Processing (ANLP)}} - -@string{+arpa1993 = {Proc.\ of the ARPA Human Language Technology Workshop}} - -@string{+arpa1994 = {Proc.\ of the ARPA Human Language Technology Workshop}} - -@string{+asialex2003 = {Proc.\ of the Asian Association for Lexicography (ASIALEX 2003)}} - -@string{+bls1988 = {Proc.\ of the 14th Annual Meeting of the Berkeley Linguistics Society}} - -@string{+bls2001 = {Proc.\ of the 27th Annual Meeting of the Berkeley Linguistics Society}} - -@string{+cicling2002 = {Proc.\ of the 3rd International Conference on Intelligent Text Processing and Computational Linguistics (CICLing-2002)}} - -@string{+cicling2003 = {Proc.\ of the 4th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing-2003)}} - -@string{+cl = {Computational Linguistics}} - -@string{+clef2003 = {Working Notes for the CLEF 2003 Workshop}} - -@string{+clin1994 = {Papers from the 4th CLIN Meeting}} - -@string{+clin2000 = {Computational Linguistics in the Netherlands 2000}} - -@string{+clin2003 = {Papers from the 14th Meeting of Computational Linguistics in the Netherlands}} - 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-@string{+emnlp2003 = {Proc.\ of the 2003 Conference on Empirical Methods in Natural Language Processing (EMNLP-2003)}} - -@string{+emnlp2004 = {Proc.\ of the 2004 Conference on Empirical Methods in Natural Language Processing (EMNLP-2004)}} - -@string{+emnlp2005 = {Proc.\ of the 2005 Conference on Empirical Methods in Natural Language Processing (EMNLP-2005)}} - -@string{+emnlp2006 = {Proc.\ of the 2006 Conference on Empirical Methods in Natural Language Processing (EMNLP-2006)}} - -@string{+emnlp2007 = {Proc.\ of the 2007 Conference on Empirical Methods in Natural Language Processing (EMNLP-2007)}} - -@string{+ewnlg1999 = {Proc.\ of the 7th European Workshop on Natural Language Generation (EWNLG'99)}} - -@string{+gl2002 = {Proc.\ of the 1st International Workshop on Generative Approaches to the Lexicon}} - -@string{+gl2003 = {Proc.\ of the 2nd International Workshop on Generative Approaches to the Lexicon}} - -@string{+hlt2001 = {Proc.\ of Human Language Technology (HLT) 2001}} - -@string{+hpsg2002 = {Proc.\ of the 9th International Conference on Head-Driven Phrase Structure Grammar (HPSG-2002)}} - -@string{+hpsg2003 = {Proc.\ of the 10th International Conference on Head-Driven Phrase Structure Grammar (HPSG-2003)}} - -@string{+icml1992 = {Proc.\ of the 9th International Machine Learning Conference}} - -@string{+icml1993 = {Proc.\ of the 10th International Conference on Machine Learning}} - -@string{+icml1994 = {Proc.\ of the 11th International Conference on Machine Learning}} - -@string{+icml1999 = {Proc.\ of the 16th International Conference on Machine Learning}} - -@string{+icslp1992 = {Proc.\ of the 2nd International Conference on Spoken Language Processing (ICSLP'92)}} - -@string{+icslp1996 = {Proc.\ of the 4th International Conference on Spoken Language Processing (ICSLP'96)}} - -@string{+icslp1998 = {Proc.\ of the 5th International Conference on Spoken Language Processing (ICSLP'98)}} - -@string{+ijcai1989 = {Proc.\ of the 11th International Joint Conference on Artificial Intelligence (IJCAI-89)}} - -@string{+ijcai1991 = {Proc.\ of the 12th International Joint Conference on Artificial Intelligence (IJCAI-91)}} - -@string{+ijcai1993 = {Proc.\ of the 13th International Joint Conference on Artificial Intelligence (IJCAI-93)}} - -@string{+ijcai1995 = {Proc.\ of the 14th International Joint Conference on Artificial Intelligence (IJCAI-95)}} - -@string{+ijcai1997 = {Proc.\ of the 15th International Joint Conference on Artificial Intelligence (IJCAI-97)}} - -@string{+ijcai1999 = {Proc.\ of the 16th International Joint Conference on Artificial Intelligence (IJCAI-99)}} - -@string{+ijcnlp2004 = {Proc.\ of the First International Joint Conference on Natural Language Processing (IJCNLP-2004)}} - -@string{+iral2003 = {Proc.\ of the The Sixth International Workshop on Information Retrieval with Asian Languages (IRAL2003)}} - -@string{+iwslt2005 = {Proc.\ of the International Workshop on Spoken Language Translation}} - -@string{+jml = {Journal of Memory and Language}} - -@string{+jnlp = {Journal of Natural Language Processing}} - -@string{+jnlp1996 = {Proc.\ of the 2nd Annual Meeting of the Association for Natural Language Processing (Japan)}} - 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-@string{+lrec2006 = {Proc.\ of the 5th International Conference on Language Resources and Evaluation (LREC-2006)}} - -@string{+lsa = {Proc.\ of the Linguistics Society of America (LSA) Annual Meeting}} - -@string{+ml = {Machine Learning}} - -@string{+mtsummit1997 = {Proc.\ of the Fifth Machine Translation Summit (MT Summit V)}} - -@string{+mtsummit2003 = {Proc.\ of the Ninth Machine Translation Summit (MT Summit IX)}} - -@string{+naacl2000 = {Proc.\ of the 1st Annual Meeting of the North American Chapter of Association for Computational Linguistics (NAACL2000)}} - -@string{+naacl2001 = {Proc.\ of the 2nd Annual Meeting of the North American Chapter of Association for Computational Linguistics (NAACL2001)}} - -@string{+naacl2001-wn = {Proc.\ of the NAACL 2001 Workshop on WordNet and Other Lexical Resources: Applications, Extensions and Customizations}} - -@string{+naacl2002 = {Proc.\ of the 40th Annual Meeting of the ACL and 3rd Annual Meeting of the NAACL (ACL-2002)}} - -@string{+naacl2003 = {Proc.\ HLT-NAACL}} - -@string{+naacl2004 = {Proc.\ of the 4th International Conference on Human Language Technology Research and 5th Annual Meeting of the NAACL (HLT-NAACL 2004)}} - -@string{+naacl2005 = {Proc.\ of the 5th International Conference on Human Language Technology Research and 6th Annual Meeting of the NAACL (HLT-NAACL 2005)}} - -@string{+naacl2006 = {Proc.\ of the 6th International Conference on Human Language Technology Research and 7th Annual Meeting of the NAACL (HLT-NAACL 2006)}} - -@string{+naacl2006-smt = {Proc.\ of the HLT-NAACL 2006 Workshop on Statistical Machine Translation}} - -@string{+naacl2007 = {Proc.\ HLT-NAACL}} - -@string{+naacl2007-ssst = {Proc.\ SSST}} - -@string{+nemlap1994 = {Proc.\ of the Conference on New Methods in Natural Language Processing}} - -@string{+nemlap1996 = {Proc.\ of the 2nd International Conference on New Methods in Natural Language Processing}} - -@string{+nemlap1998 = {Proc.\ of the Joint Conference on New Methods in Natural Language Processing and Natural Language Learning (NeMLaP3/CoNLL-98)}} - 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-@string{+sigir1990 = {Proc.\ of 13th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'90)}} - -@string{+sigir1993 = {Proc.\ of 16th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'93)}} - -@string{+sigir1994 = {Proc.\ of 17th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'94)}} - -@string{+sigir1995 = {Proc.\ of 18th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'95)}} - -@string{+sigir1996 = {Proc.\ of 19th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'96)}} - -@string{+sigir1997 = {Proc.\ of 20th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'97)}} - -@string{+sigir1998 = {Proc.\ of 21st International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'98)}} - -@string{+sigir1999 = {Proc.\ of 22nd International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'99)}} - -@string{+sigir2000 = {Proc.\ of 23rd International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2000)}} - -@string{+sigir2001 = {Proc.\ of 24th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2001)}} - -@string{+sigsemprep2003 = {Proc.\ of the ACL-SIGSEM Workshop on the Linguistic Dimensions of Prepositions and their Use in Computational Linguistics Formalisms and Applications}} - -@string{+sigsemprep2005 = {Proc.\ of the Second ACL-SIGSEM Workshop on the Linguistic Dimensions of Prepositions and their Use in Computational Linguistics Formalisms and Applications}} - -@string{+taln1999 = {Actes de la 6e Conf\'erence annuelle sur le Traitement Automatique des Langues Naturelles (TALN '99)}} - -@string{+tmi1993 = {Proc.\ of the 5th International Conference on Theoretical and Methodological Issues in Machine Translation (TMI-93)}} - -@string{+tmi1995 = {Proc.\ of the 6th International Conference on Theoretical and Methodological Issues in Machine Translation (TMI-95)}} - -@string{+tmi1997 = {Proc.\ of the 7th International Conference on Theoretical and Methodological Issues in Machine Translation (TMI-97)}} - -@string{+tmi1999 = {Proc.\ of the 8th International Conference on Theoretical and Methodological Issues in Machine Translation (TMI-99)}} - -@string{+tmi2002 = {Proc.\ of the 9th International Conference on Theoretical and Methodological Issues in Machine Translation (TMI 2002)}} - -@string{+trec1999 = {Proc.\ of the 7th Text REtrieval Conference (TREC-7)}} - -@string{+trec2000 = {Proc.\ of the 8th Text REtrieval Conference (TREC-8)}} - -@string{+wcn1994 = {Proc.\ of the Workshop on Compound Nouns: Multilingual Aspects of Nominal Composition}} - -@string{+wmt2008 = {Proc.\ of the Third Workshop on Machine Translation}} - -@string{+wvlc1993 = {Proc.\ of the Workshop on Very Large Corpora: Academic and Industrial Perspectives}} - -@string{+wvlc1994 = {Proc.\ of the 2nd Annual Workshop on Very Large Corpora}} - -@string{+wvlc1995 = {Proc.\ of the 3rd Annual Workshop on Very Large Corpora}} - -@string{+wvlc1996 = {Proc.\ of the 4th Annual Workshop on Very Large Corpora}} - -@string{+wvlc1997 = {Proc.\ of the 5th Annual Workshop on Very Large Corpora}} - -@string{+wvlc1998 = {Proc.\ of the 6th Annual Workshop on Very Large Corpora}} - -@string{ajcl = {American Journal of Computational Linguistics}} - - -@inbook{klein04hypergraph, - Address = {Norwell, MA, USA}, - Author = {Klein, Dan and Manning, Christopher D.}, - Book = {New developments in parsing technology}, - Date-Added = {2009-11-29 15:52:20 +0000}, - Date-Modified = {2009-11-29 15:52:33 +0000}, - Isbn = {1-4020-2293-X}, - Pages = {351--372}, - Publisher = {Kluwer Academic Publishers}, - Title = {Parsing and hypergraphs}, - Year = {2004}} - -@inproceedings{vangael08beam, - Abstract = {The infinite hidden Markov model is a non-parametric extension of the widely used hidden Markov model. Our paper introduces a new inference algorithm for the infinite Hidden Markov model called beam sampling . Beam sampling combines slice sampling, which limits the number of states considered at each time step to a finite number, with dynamic programming, which samples whole state trajectories efficiently. Our algorithm typically outperforms the Gibbs sampler and is more robust. We present applications of iHMM inference using the beam sampler on changepoint detection and text prediction problems.}, - Address = {New York, NY, USA}, - Author = {Van Gael, Jurgen and Saatci, Yunus and Teh, Yee W. and Ghahramani, Zoubin}, - Booktitle = {ICML}, - Citeulike-Article-Id = {5943766}, - Citeulike-Linkout-0 = {http://portal.acm.org/citation.cfm?id=1390156.1390293}, - Citeulike-Linkout-1 = {http://dx.doi.org/10.1145/1390156.1390293}, - Date-Added = {2009-11-29 13:51:26 +0000}, - Date-Modified = {2009-11-29 13:51:50 +0000}, - Doi = {10.1145/1390156.1390293}, - Isbn = {978-1-60558-205-4}, - Keywords = {dirichlet-process, mcmc, model, slice-sampling}, - Location = {Helsinki, Finland}, - Pages = {1088--1095}, - Posted-At = {2009-11-12 20:41:25}, - Priority = {2}, - Title = {Beam sampling for the infinite hidden Markov model}, - Url = {http://dx.doi.org/10.1145/1390156.1390293}, - Year = {2008}, - Bdsk-Url-1 = {http://dx.doi.org/10.1145/1390156.1390293}} - -@inproceedings{blunsom09acl, - Address = {Suntec, Singapore}, - Author = {Blunsom, Phil and Cohn, Trevor and Dyer, Chris and Osborne, Miles}, - Booktitle = {Proc. ACL/IJCNLP}, - Month = {August}, - Pages = {782--790}, - Publisher = {Association for Computational Linguistics}, - Title = {A {G}ibbs Sampler for Phrasal Synchronous Grammar Induction}, - Url = {http://www.aclweb.org/anthology/P/P09/P09-1088}, - Year = {2009}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/P/P09/P09-1088}} - -@article{neal03slice, - Author = {Radford Neal}, - Date-Added = {2009-11-28 22:31:06 +0000}, - Date-Modified = {2009-11-28 22:32:26 +0000}, - Journal = {Annals of Statistics}, - Pages = {705--767}, - Title = {Slice Sampling}, - Volume = {31}, - Year = {2003}} - -@inproceedings{joshua09, - Address = {Athens, Greece}, - Author = {Zhifei Li and Chris Callison-Burch and Chris Dyer and Sanjeev Khudanpur and Lane Schwartz and Wren Thornton and Jonathan Weese and Omar Zaidan}, - Booktitle = {Proc. of the Fourth Workshop on Statistical Machine Translation}, - Date-Added = {2009-11-03 12:24:15 +0000}, - Date-Modified = {2009-11-03 12:24:40 +0000}, - Month = {March}, - Pages = {135--139}, - Publisher = {Association for Computational Linguistics}, - Title = {Joshua: An Open Source Toolkit for Parsing-Based Machine Translation}, - Url = {http://www.aclweb.org/anthology/W/W09/W09-0x24}, - Year = {2009}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/W/W09/W09-0x24}} - -@inproceedings{cohn09naacl, - Address = {Morristown, NJ, USA}, - Author = {Cohn, Trevor and Goldwater, Sharon and Blunsom, Phil}, - Booktitle = {NAACL '09: Proc. of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics on ZZZ}, - Date-Added = {2009-10-30 16:03:09 +0000}, - Date-Modified = {2009-10-30 16:03:18 +0000}, - Isbn = {978-1-932432-41-1}, - Location = {Boulder, Colorado}, - Pages = {548--556}, - Publisher = {Association for Computational Linguistics}, - Title = {Inducing compact but accurate tree-substitution grammars}, - Year = {2009}} - -@inproceedings{blunsom09acl_short, - Address = {Suntec, Singapore}, - Author = {Blunsom, Phil and Cohn, Trevor and Goldwater, Sharon and Johnson, Mark}, - Booktitle = {Proc. of the ACL-IJCNLP 2009 Conference Short Papers}, - Date-Added = {2009-10-30 15:59:35 +0000}, - Date-Modified = {2009-10-30 15:59:49 +0000}, - Month = {August}, - Pages = {337--340}, - Publisher = {Association for Computational Linguistics}, - Title = {A Note on the Implementation of Hierarchical Dirichlet Processes}, - Url = {http://www.aclweb.org/anthology/P/P09/P09-2085}, - Year = {2009}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/P/P09/P09-2085}} - -@inproceedings{arun09conll, - Address = {Morristown, NJ, USA}, - Author = {Arun, Abhishek and Dyer, Chris and Haddow, Barry and Blunsom, Phil and Lopez, Adam and Koehn, Philipp}, - Booktitle = {CoNLL '09: Proc. of the Thirteenth Conference on Computational Natural Language Learning}, - Date-Added = {2009-10-30 15:56:30 +0000}, - Date-Modified = {2009-10-30 15:57:33 +0000}, - Isbn = {978-1-932432-29-9}, - Location = {Boulder, Colorado}, - Pages = {102--110}, - Publisher = {Association for Computational Linguistics}, - Title = {Monte carlo inference and maximization for phrase-based translation}, - Year = {2009}} - -@inproceedings{cohn09emnlp, - Address = {Singapore}, - Author = {Cohn, Trevor and Blunsom, Phil}, - Booktitle = {Proc\. EMNLP-09}, - Citeulike-Article-Id = {5427393}, - Citeulike-Linkout-0 = {http://www.aclweb.org/anthology-new/D/D09/D09-1037.bib}, - Citeulike-Linkout-1 = {http://www.aclweb.org/anthology-new/D/D09/D09-1037.pdf}, - Date-Added = {2009-10-30 15:53:43 +0000}, - Date-Modified = {2009-10-30 15:54:28 +0000}, - Keywords = {emnlp2009}, - Month = {August}, - Pages = {352--361}, - Posted-At = {2009-08-12 16:03:51}, - Priority = {2}, - Title = {A {Bayesian} Model of Syntax-Directed Tree to String Grammar Induction}, - Url = {http://www.aclweb.org/anthology-new/D/D09/D09-1037.bib}, - Year = {2009}, - Bdsk-File-1 = {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}} - -@inproceedings{blunsom06question, - Address = {New York, NY, USA}, - Author = {Blunsom, Phil and Kocik, Krystle and Curran, James R.}, - Booktitle = {SIGIR '06: Proc. of the 29th annual international ACM SIGIR conference on Research and development in information retrieval}, - Date-Added = {2009-10-30 15:26:07 +0000}, - Date-Modified = {2009-10-30 15:26:39 +0000}, - Doi = {http://doi.acm.org/10.1145/1148170.1148282}, - Isbn = {1-59593-369-7}, - Location = {Seattle, Washington, USA}, - Pages = {615--616}, - Publisher = {ACM}, - Title = {Question classification with log-linear models}, - Year = {2006}, - Bdsk-File-1 = {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}} - 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Duffy}, - Booktitle = +ACL2002, - Title = {New ranking algorithms for parsing and tagging: Kernels over discrete structures}, - Url = {citeseer.ist.psu.edu/article/collins02new.html}, - Year = {2002}, - Bdsk-Url-1 = {citeseer.ist.psu.edu/article/collins02new.html}} - -@inproceedings{ayan06cper, - Address = {Sydney, Australia}, - Author = {Ayan, Necip Fazil and Dorr, Bonnie J.}, - Booktitle = +ACL2006, - Month = {July}, - Pages = {9--16}, - Title = {Going Beyond {AER}: An Extensive Analysis of Word Alignments and Their Impact on {MT}}, - Url = {http://www.aclweb.org/anthology/P/P06/P06-1002}, - Year = {2006}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/P/P06/P06-1002}} - -@inproceedings{fraser06, - Address = {Sydney, Australia}, - Author = {Fraser, Alexander and Marcu, Daniel}, - Booktitle = +ACL2006, - Month = {July}, - Pages = {769--776}, - Publisher = {Association for Computational Linguistics}, - Title = {Semi-Supervised Training for Statistical Word Alignment}, - Url = {http://www.aclweb.org/anthology/P/P06/P06-1097}, - Year = {2006}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/P/P06/P06-1097}} - -@techreport{fraser06measure, - Author = {Alexander Fraser and Daniel Marcu}, - Institution = {ISI/University of Southern California}, - Month = May, - Title = {Measuring Word Alignment Quality for Statistical Machine Translation}, - Type = {ISI-TR-616 tecnical report}, - Year = 2006} - -@techreport{papineni01bleu, - Author = {K. 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Proc. of the 1998 IEEE International Conference on}, - Pages = {189-192 vol.1}, - Title = {Maximum likelihood and discriminative training of direct translation models}, - Volume = {1}, - Year = {12-15 May 1998}} - -@inproceedings{koehn04pharaoh, - Author = {Philipp Koehn}, - Booktitle = {Proc.\ of the AMTA-2004}, - Title = {Pharaoh: a Beam Search Decoder for Phrase-Based Statistical Machine Translation Models}, - Year = {2004}} - -@inproceedings{koehn07moses, - Address = {Prague}, - Author = {Philipp Koehn and Hieu Hoang and Alexandra Birch and Chris Callison-Burch and Marcello Federico and Nicola Bertoldi and Brooke Cowan and Wade Shen and Christine Moran and Richard Zens and Chris Dyer and Ondrej Bojar and Alexandra Constantin and Evan Herbst}, - Booktitle = +ACL2007, - Title = {Moses: Open Source Toolkit for Statistical Machine Translation}, - Year = {2007}} - -@article{bangalore99supertagging, - Author = {Srinivas Bangalore and Aravind K. Joshi}, - Journal = {Computational Linguistics}, - Number = {2}, - Pages = {237-265}, - Title = {Supertagging: An Approach to Almost Parsing}, - Url = {citeseer.ist.psu.edu/bangalore99supertagging.html}, - Volume = {25}, - Year = {1999}, - Bdsk-Url-1 = {citeseer.ist.psu.edu/bangalore99supertagging.html}} - -@inproceedings{hockenmaier02ccgbank, - Address = {Las Palmas, Spain}, - Author = {Julia Hockenmaier and Mark Steedman}, - Booktitle = +LREC2002, - Pages = {1974--1981}, - Title = {Acquiring Compact Lexicalized Grammars from a Cleaner Treebank}, - Url = {citeseer.ist.psu.edu/531192.html}, - Year = {2002}, - Bdsk-Url-1 = {citeseer.ist.psu.edu/531192.html}} - -@inproceedings{Copestake:Flickinger:2000, - Address = {Athens, Greece}, - Author = {Ann Copestake and Dan Flickinger}, - Booktitle = +LREC2000, - Title = {An open-source grammar development environment and broad-coverage {English} grammar using {HPSG}}, - Year = 2000} - -@incollection{Flickinger:2002, - Author = {Dan Flickinger}, - Crossref = {_CollaborativeLangEng}, - Title = {On building a more efficient grammar by exploiting types}} - -@book{_CollaborativeLangEng, - Address = {Stanford, USA}, - Booktitle = {Collaborative Language Engineering}, - Editor = {Stephan Oepen and Dan Flickinger and Jun'ichi Tsujii and Hans Uszkoreit}, - Publisher = {CSLI Publications}, - Title = {Collaborative Language Engineering}, - Year = 2002} - -@inproceedings{Uszkoreit:2002, - Address = {Taipei, Taiwan}, - Author = {Hans Uszkoreit}, - Booktitle = +COLING2002, - Title = {New Chances for Deep Linguistic Processing}, - Year = {2002}} - -@book{Butt+:1999, - Address = {Stanford, USA}, - Author = {Miriam Butt and Tracy {Holloway King} and Maria-Eugenia Nino and Frederique Segond}, - Publisher = {CSLI Publications}, - Title = {A Grammar Writer's Cookbook}, - Year = 1999} - -@inproceedings{Bos+:2004, - Address = {Geneva, Switzerland}, - Author = {Johan Bos and Stephen Clark and Mark Steedman and James R. Curran and Julia Hockenmaier}, - Booktitle = +COLING2004, - Pages = {1240--7}, - Title = {Wide-Coverage Semantic Representations from a {CCG} Parser}, - Year = 2004} - -@inproceedings{vanNoord:2004, - Address = {Barcelona, Spain}, - Author = {Gertjan {van Noord}}, - Booktitle = +ACL2004, - Title = {Error Mining for Wide-Coverage Grammar Engineering}, - Year = 2004} - -@inproceedings{zhang:kordoni:2006, - Address = {Genoa, Italy}, - Author = {Yi Zhang and Valia Kordoni}, - Booktitle = +LREC2006, - Title = {Automated Deep Lexical Acquisition for Robust Open Texts Processing}, - Year = {2006}} - -@inproceedings{zhang-kordoni:2005:ALTA2005, - Address = {Sydney, Australia}, - Author = {Yi Zhang and Valia Kordoni}, - Booktitle = {Proc.\ of the Australasian Language Technology Workshop 2005}, - Pages = {24--31}, - Title = {A Statistical Approach towards Unknown Word Type Prediction for Deep Grammars}, - Year = {2005}} - -@inproceedings{blunsom04srl, - Address = {Sydney, Australia}, - Author = {Phil Blunsom}, - Booktitle = {Proc.\ of the Australasian Language Technology Workshop 2004}, - Pages = {109--116}, - Title = {Maximum Entropy {M}arkov models for semantic role labelling}, - Year = {2005}} - -@inproceedings{blunsom06supertagging, - Address = {Sydney, Australia}, - Author = {Blunsom, Phil and Baldwin, Timothy}, - Booktitle = {Proc. of the 2006 Conference on Empirical Methods in Natural Language Processing}, - Month = {July}, - Pages = {164--171}, - Title = {Multilingual Deep Lexical Acquisition for {HPSG}s via Supertagging}, - Year = {2006}, - Bdsk-File-1 = {YnBsaXN0MDDUAQIDBAUIJidUJHRvcFgkb2JqZWN0c1gkdmVyc2lvblkkYXJjaGl2ZXLRBgdUcm9vdIABqAkKFRYXGyIjVSRudWxs0wsMDQ4RFFpOUy5vYmplY3RzV05TLmtleXNWJGNsYXNzog8QgASABqISE4ACgAOAB1lhbGlhc0RhdGFccmVsYXRpdmVQYXRo0hgNGRpXTlMuZGF0YU8RAdgAAAAAAdgAAgAADE1hY2ludG9zaCBIRAAAAAAAAAAAAAAAAAAAAMarigZIKwAAACDEGhBzdXBlcnRhZ2dpbmcucGRmAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAIMQcxxBqrwAAAAAAAAAAAAMABQAACSAAAAAAAAAAAAAAAAAAAAAEcHVicwAQAAgAAMare/YAAAARAAgAAMcQaq8AAAABABwAIMQaACC8VwAgvD0AIFfBAAr3ewAJOnoAAJDnAAIAWU1hY2ludG9zaCBIRDpVc2VyczpwYmx1bnNvbTp3b3Jrc3BhY2U6aG9tZXBhZ2U6Y2xnLm94LmFjLnVrOmJsdW5zb206cHViczpzdXBlcnRhZ2dpbmcucGRmAAAOACIAEABzAHUAcABlAHIAdABhAGcAZwBpAG4AZwAuAHAAZABmAA8AGgAMAE0AYQBjAGkAbgB0AG8AcwBoACAASABEABIATFVzZXJzL3BibHVuc29tL3dvcmtzcGFjZS9ob21lcGFnZS9jbGcub3guYWMudWsvYmx1bnNvbS9wdWJzL3N1cGVydGFnZ2luZy5wZGYAEwABLwAAFQACAA///wAAgAXSHB0eH1gkY2xhc3Nlc1okY2xhc3NuYW1lox8gIV1OU011dGFibGVEYXRhVk5TRGF0YVhOU09iamVjdF8QPC4uLy4uLy4uL2hvbWVwYWdlL2NsZy5veC5hYy51ay9ibHVuc29tL3B1YnMvc3VwZXJ0YWdnaW5nLnBkZtIcHSQloiUhXE5TRGljdGlvbmFyeRIAAYagXxAPTlNLZXllZEFyY2hpdmVyAAgAEQAWAB8AKAAyADUAOgA8AEUASwBSAF0AZQBsAG8AcQBzAHYAeAB6AHwAhgCTAJgAoAJ8An4CgwKMApcCmwKpArACuQL4Av0DAAMNAxIAAAAAAAACAQAAAAAAAAAoAAAAAAAAAAAAAAAAAAADJA==}} - -@inproceedings{Ben:Fli:Oep:02, - Address = {Taipei, Taiwan}, - Author = {Emily M. Bender and Dan Flickinger and Stephan Oepen}, - Booktitle = +COLING2002-GEE, - Title = {The Grammar {M}atrix. {A}n Open-Source Starter-Kit for the Rapid Development of Cross-Linguistically Consistent Broad-Coverage Precision Grammar}, - Year = 2002} - -@inproceedings{Riezler:2002, - Address = {Philadelphia, USA}, - Author = {Stefan Riezler and Tracy H. King and Ronald M. Kaplan and Richard Crouch and John T. {Maxwell III} and Mark Johnson}, - Booktitle = +ACL2002, - Title = {Parsing the {Wall Street Journal} using a {Lexical-Functional Grammar} and Discriminative Estimation Techniques}, - Year = 2002} - -@incollection{Baldwin+:2005b, - Author = {Timothy Baldwin and Emily M. Bender and Dan Flickinger and Ara Kim and Stephan Oepen}, - Crossref = {_Kepser:Reis:2005}, - Title = {Beauty and the Beast: What running a broad-coverage precision grammar over the {BNC} taught us about the grammar --- and the corpus}} - -@inproceedings{Baldwin:2005d, - Address = {Ann Arbor, USA}, - Author = {Timothy Baldwin}, - Booktitle = +ACL2005-DLA, - Pages = {67--76}, - Title = {Bootstrapping Deep Lexical Resources: Resources for Courses}, - Year = 2005} - -@inproceedings{Baldwin:2005e, - Address = {Tokyo, Japan}, - Author = {Timothy Baldwin}, - Booktitle = +PACLING2005, - Note = {(Invited Paper)}, - Pages = {23--32}, - Title = {General-Purpose Lexical Acquisition: Procedures, Questions and Results}, - Year = {2005}} - -@phdthesis{Fouvry:2003b, - Author = {Frederik Fouvry}, - School = {University of Essex}, - Title = {Robust Processing for Constraint-based Grammar Formalisms}, - Year = 2003} - -@inproceedings{Lapata:Keller:04, - Address = {Boston, USA}, - Author = {Mirella Lapata and Frank Keller}, - Booktitle = +NAACL2004, - Pages = {121--8}, - Title = {The Web as a Baseline: Evaluating the Performance of Unsupervised Web-based Models for a Range of {NLP} Tasks}, - Year = {2004}} - -@phdthesis{Korhonen:2002, - Author = {Anna Korhonen}, - School = {University of Cambridge}, - Title = {Subcategorization Acquisition}, - Year = 2002} - -@inproceedings{Joanis:2003, - Address = {Budapest, Hungary}, - Author = {Eric Joanis and Suzanne Stevenson}, - Booktitle = +EACL2003, - Pages = {163--70}, - Title = {A general feature space for automatic verb classification}, - Year = 2003} - -@book{Pollard:Sag:1994, - Address = {Chicago, USA}, - Author = {Carl Pollard and Ivan A. 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Rabiner}, - Book = {Readings in speech recognition}, - Isbn = {1-55860-124-4}, - Pages = {267--296}, - Publisher = {Morgan Kaufmann Publishers Inc.}, - Title = {A tutorial on hidden {M}arkov models and selected applications in speech recognition}, - Year = {1990}} - -@inproceedings{koehn04statistical, - Address = {Barcelona, Spain}, - Author = {Philipp Koehn}, - Booktitle = +EMNLP2004, - Month = {July}, - Title = {Statistical significance tests for machine translation evaluation}, - Url = {citeseer.ist.psu.edu/koehn04statistical.html}, - Year = {2004}, - Bdsk-Url-1 = {citeseer.ist.psu.edu/koehn04statistical.html}} - -@inproceedings{mccallum03ne, - Address = {Edmonton, Canada}, - Author = {Andrew McCallum and Wei Li}, - Booktitle = +NAACL2003, - Pages = {188--191}, - Title = {Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons}, - Year = {2003}} - -@inproceedings{sha03shallow, - Address = {Edmonton, Canada}, - Author = {Fei Sha and Fernando Pereira}, - Booktitle = +NAACL2003, - Pages = {134--141}, - Title = {Shallow parsing with conditional random fields}, - Year = {2003}} - -@inproceedings{peng04accurate, - Author = {F. Peng and A. McCallum}, - Booktitle = +NAACL2004, - Pages = {329--336}, - Title = {Accurate information extraction from research papers using conditional random fields}, - Url = {citeseer.ist.psu.edu/peng04accurate.html}, - Year = {2004}, - Bdsk-Url-1 = {citeseer.ist.psu.edu/peng04accurate.html}} - -@inproceedings{cohn05srl, - Address = {Ann Arbor, Michigan}, - Author = {Cohn, Trevor and Blunsom, Philip}, - Booktitle = +CONLL2005, - Month = {June}, - Pages = {169--172}, - Title = {Semantic Role Labelling with Tree Conditional Random Fields}, - Url = {http://www.aclweb.org/anthology/W/W05/W05-0622}, - Year = {2005}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/W/W05/W05-0622}} - -@inproceedings{blunsom06wa, - Address = {Sydney, Australia}, - Author = {Blunsom, Phil and Cohn, Trevor}, - Booktitle = +ACL2006, - Month = {July}, - Pages = {65--72}, - Title = {Discriminative Word Alignment with Conditional Random Fields}, - Url = {http://www.aclweb.org/anthology/P/P06/P06-1009}, - Year = {2006}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/P/P06/P06-1009}} - -@inproceedings{blunsom08latent, - Address = {Columbus, Ohio}, - Author = {Blunsom, Phil and Cohn, Trevor and Osborne, Miles}, - Booktitle = +ACL2008, - Month = {June}, - Pages = {200--208}, - Title = {A Discriminative Latent Variable Model for Statistical Machine Translation}, - Url = {http://www.aclweb.org/anthology/P/P08/P08-1024}, - Year = {2008}, - Bdsk-File-1 = {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}} - -@inproceedings{blunsom08bscfg, - Address = {Vancouver, Canada}, - Author = {Blunsom, Phil and Cohn, Trevor and Osborne, Miles}, - Booktitle = {Proc. of NIPS 21}, - Month = {December}, - Title = {{B}ayesian Synchronous Grammar Induction}, - Year = {2008}, - Bdsk-File-1 = {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}} - -@inproceedings{blunsom08inference, - Address = {Honolulu, Hawaii}, - Author = {Blunsom, Phil and Osborne, Miles}, - Booktitle = {Proc. of the 2008 Conference on Empirical Methods in Natural Language Processing}, - Month = {October}, - Pages = {215--223}, - Title = {Probabilistic Inference for Machine Translation}, - Year = {2008}, - Bdsk-File-1 = {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}} - 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ACM}, - Number = {3}, - Pages = {465--488}, - Publisher = {ACM}, - Title = {Syntax-Directed Transduction}, - Volume = {15}, - Year = {1968}, - Bdsk-Url-1 = {http://doi.acm.org/10.1145/321466.321477}} - -@inproceedings{watanabe06gnf, - Address = {Sydney, Australia}, - Author = {Taro Watanabe and Hajime Tsukada and Hideki Isozaki}, - Booktitle = +ACL2006, - Pages = {777--784}, - Title = {Left-to-right target generation for hierarchical phrase-based translation}, - Year = {2006}} - -@inproceedings{watanabe07online, - Address = {Prague, Czech Republic}, - Author = {Watanabe, Taro and Suzuki, Jun and Tsukada, Hajime and Isozaki, Hideki}, - Booktitle = +EMNLP2007, - Pages = {764--773}, - Title = {Online Large-Margin Training for Statistical Machine Translation}, - Year = {2007}} - -@inproceedings{carpuat07wsd, - Address = {Prague, Czech Republic}, - Author = {Carpuat, Marine and Wu, Dekai}, - Booktitle = +EMNLP2007, - Pages = {61--72}, - Title = {Improving Statistical Machine Translation Using Word Sense Disambiguation}, - Year = {2007}} - -@inproceedings{wang07, - Address = {Prague, Czech Republic}, - Author = {Wang, Chao and Collins, Michael and Koehn, Philipp}, - Booktitle = +EMNLP2007, - Pages = {737--745}, - Title = {{C}hinese Syntactic Reordering for Statistical Machine Translation}, - Url = {http://www.aclweb.org/anthology/D/D07/D07-1077}, - Year = {2007}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/D/D07/D07-1077}} - -@inproceedings{denero06generative, - Address = {New York City}, - Author = {DeNero, John and Gillick, Dan and Zhang, James and Klein, Dan}, - Booktitle = +NAACL2006-SMT, - Date-Modified = {2009-10-22 14:34:55 +0100}, - Month = {June}, - Pages = {31--38}, - Read = {Yes}, - Title = {Why Generative Phrase Models Underperform Surface Heuristics}, - Year = {2006}, - Bdsk-File-1 = {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}} - -@inproceedings{zollmann06syntax, - Address = {New York City}, - Author = {Andreas Zollmann and Ashish Venugopal}, - Booktitle = +NAACL2006-SMT, - Month = {June}, - Title = {Syntax augmented machine translation via chart parsing}, - Year = {2006}} - -@article{johnson02dop, - Author = {Mark Johnson}, - Journal = {Computational Linguistics}, - Number = {1}, - Pages = {71--76}, - Title = {The {DOP} Estimation Method Is Biased and Inconsistent}, - Volume = {28}, - Year = {2002}} - -@phdthesis{beal03, - Author = {Matthew Beal}, - School = {The Gatsby Computational Neuroscience Unit, University College London}, - Title = {Variational Algorithms for Approximate Bayesian Inference}, - Year = {2003}} - -@inproceedings{eck05iwslt, - Address = {Pittsburgh}, - Author = {Matthias Eck and Chiori Hori}, - Booktitle = +IWSLT2005, - Month = {October}, - Title = {Overview of the {IWSLT} 2005 Evaluation Campaign}, - Year = {2005}} - -@inproceedings{cherry07itg, - Address = {Rochester, USA}, - Author = {Colin Cherry and Dekany Lin}, - Booktitle = +NAACL2007-SSST, - Title = {Inversion Transduction Grammar for Joint Phrasal Translation Modeling}, - Year = {2007}} - -@article{teh06hdp, - Author = {Y. 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Goodman}, - Isbn = {0-591-85426-0}, - Note = {Adviser-Stuart Shieber}, - Order_No = {AAI9832377}, - Publisher = {Harvard University}, - Title = {Parsing inside-out}, - Year = {1998}} - -@inproceedings{mi08forest, - Address = {Columbus, Ohio}, - Author = {Mi, Haitao and Huang, Liang and Liu, Qun}, - Booktitle = +ACL2008, - Month = {June}, - Pages = {192--199}, - Title = {Forest-Based Translation}, - Url = {http://www.aclweb.org/anthology/P/P08/P08-1023}, - Year = {2008}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/P/P08/P08-1023}} - -@inproceedings{huang06syntax, - Address = {Boston, MA}, - Author = {Huang, Liang and Knight, Kevin and Joshi, Aravind}, - Booktitle = {In Proc. of the 7th Biennial Conference of the Association for Machine Translation in the Americas ({AMTA})}, - Title = {Statistical Syntax-Directed Translation with Extended Domain of Locality}, - Year = {2006}} - -@inproceedings{kumar04mbr, - Author = {Shankar Kumar and William Byrne}, - Booktitle = +NAACL2004, - Pages = {169--176}, - Title = {Minimum bayes-risk decoding for statistical machine translation}, - Year = {2004}} - -@inproceedings{zhang08bitg, - Address = {Columbus, Ohio}, - Author = {Zhang, Hao and Quirk, Chris and Moore, Robert C. and Gildea, Daniel}, - Booktitle = +ACL2008, - Month = {June}, - Pages = {97--105}, - Title = {{Bayesian} Learning of Non-Compositional Phrases with Synchronous Parsing}, - Year = {2008}} - -@inproceedings{newman07distributed, - Author = {David Newman and Arthur Asuncion and Padhraic Smyth and Max Welling}, - Booktitle = {NIPS}, - Publisher = {MIT Press}, - Title = {Distributed Inference for Latent Dirichlet Allocation.}, - Year = {2007}} - -@inproceedings{asuncion08asynchronous, - Author = {Arthur Asuncion and Padhraic Smyth and Max Welling}, - Booktitle = {NIPS}, - Publisher = {MIT Press}, - Title = {Asynchronous Distributed Learning of Topic Models.}, - Year = {2008}} - -@inproceedings{johnson07, - Address = {Rochester, New York}, - Author = {Johnson, Mark and Griffiths, Thomas and Goldwater, Sharon}, - Booktitle = +NAACL2007, - Month = {April}, - Pages = {139--146}, - Title = {{Bayesian} Inference for {PCFG}s via {Markov} Chain {Monte} {Carlo}}, - Url = {http://www.aclweb.org/anthology/N/N07/N07-1018}, - Year = {2007}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/N/N07/N07-1018}} - -@inproceedings{johnson07pos, - Address = {Prague, Czech Republic}, - Author = {Johnson, Mark}, - Booktitle = +EMNLP2007, - Pages = {296--305}, - Title = {Why Doesnt {EM} Find Good {HMM} {POS}-Taggers?}, - Year = {2007}} - -@inproceedings{denero08complexity, - Address = {Columbus, Ohio}, - Author = {DeNero, John and Klein, Dan}, - Booktitle = {Proc. of ACL-08: HLT, Short Papers}, - Month = {June}, - Pages = {25--28}, - Publisher = {Association for Computational Linguistics}, - Title = {The Complexity of Phrase Alignment Problems}, - Url = {http://www.aclweb.org/anthology/P/P08/P08-2007}, - Year = {2008}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/P/P08/P08-2007}} - -@inproceedings{denero08sampling, - Address = {Honolulu, Hawaii}, - Author = {DeNero, John and Bouchard-C\^{o}t\'{e}, Alexandre and Klein, Dan}, - Booktitle = {Proc. EMNLP}, - Month = {October}, - Pages = {314--323}, - Title = {Sampling Alignment Structure under a {B}ayesian Translation Model}, - Url = {http://www.aclweb.org/anthology/D08-1033}, - Year = {2008}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/D08-1033}} - -@inproceedings{birch06constraining, - Address = {New York City}, - Author = {Birch, Alexandra and Callison-Burch, Chris and Osborne, Miles and Koehn, Philipp}, - Booktitle = {Proc. on the Workshop on Statistical Machine Translation}, - Month = {June}, - Pages = {154--157}, - Publisher = {Association for Computational Linguistics}, - Title = {Constraining the Phrase-Based, Joint Probability Statistical Translation Model}, - Url = {http://www.aclweb.org/anthology/W/W06/W06-3123}, - Year = {2006}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/W/W06/W06-3123}} - -@inproceedings{chang08chinese, - Address = {Prague, Czech Republic}, - Author = {Chang, Pi-Chuan and Jurafsky, Dan and Manning, Christopher D.}, - Booktitle = +WMT2008, - Month = {June}, - Title = {Optimizing {C}hinese Word Segmentation for Machine Translation Performance}, - Year = {2008}} - -@inproceedings{habash06preprocessing, - Address = {New York City}, - Author = {Habash, Nizar and Sadat, Fatiha}, - Booktitle = +NAACL2006, - Publisher = {Association for Computational Linguistics}, - Title = {Arabic Preprocessing Schemes for Statistical Machine Translation}, - Year = {2006}} - -@inproceedings{goldwater07, - Address = {Prague, Czech Republic}, - Author = {Goldwater, Sharon and Griffiths, Tom}, - Booktitle = +ACL2007, - Month = {June}, - Pages = {744--751}, - Title = {A fully Bayesian approach to unsupervised part-of-speech tagging}, - Url = {http://www.aclweb.org/anthology/P/P07/P07-1094}, - Year = {2007}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/P/P07/P07-1094}} - -@inproceedings{goldwater06, - Address = {Sydney}, - Author = {Goldwater, Sharon and Griffiths, Tom and Johnson, Mark}, - Booktitle = +ACL2006, - Title = {Contextual Dependencies in Unsupervised Word Segmentation}, - Year = {2006}} - -@incollection{goldwater06interpolating, - Address = {Cambridge, MA}, - Author = {Sharon Goldwater and Tom Griffiths and Mark Johnson}, - Booktitle = {Advances in Neural Information Processing Systems 18}, - Editor = {Y. Weiss and B. Sch\"{o}lkopf and J. Platt}, - Pages = {459--466}, - Publisher = {MIT Press}, - Title = {Interpolating between types and tokens by estimating power-law generators}, - Year = {2006}} - -@inproceedings{zhang08factorisation, - Address = {Manchester, UK}, - Author = {Zhang, Hao and Gildea, Daniel and Chiang, David}, - Booktitle = +COLING2008, - Pages = {1081--1088}, - Title = {Extracting Synchronous Grammar Rules From Word-Level Alignments in Linear Time}, - Year = {2008}} - -@article{antoniak74, - Author = {Antoniak, Charles E.}, - Journal = {The Annals of Statistics}, - Number = {6}, - Pages = {1152--1174}, - Title = {Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric Problems}, - Volume = {2}, - Year = {1974}} - -@phdthesis{blunsom07thesis, - Author = {Blunsom, Phil}, - School = {Department of Computer Science and Software Engineering, The University of Melbourne}, - Title = {Structured Classification for Multilingual Natural Language Processing}, - Year = {2007}} - -@phdthesis{RL:1, - Address = {Stanford, California}, - Author = {R. E. Larson}, - School = {Stanford University}, - Title = {Title of Dissertation}, - Year = 1964} - -@incollection{aldous85, - Author = {Aldous, D.}, - Booktitle = {\'{E}cole d'\'{E}t\'{e} de Probabiliti\'{e}s de Saint-Flour XIII 1983}, - Pages = {1--198}, - Publisher = {Springer}, - Title = {Exchangeability and related topics}, - Year = {1985}} - -@incollection{blunsom09scfg, - Author = {Phil Blunsom and Trevor Cohn and Miles Osborne}, - Booktitle = {Advances in Neural Information Processing Systems 21}, - Editor = {D. Koller and D. Schuurmans and Y. Bengio and L. Bottou}, - Pages = {161--168}, - Title = {Bayesian Synchronous Grammar Induction}, - Year = {2009}, - Bdsk-File-1 = {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}} - -@inproceedings{zhang06synchronous, - Author = {Zhang,, Hao and Huang,, Liang and Gildea,, Daniel and Knight,, Kevin}, - Booktitle = +NAACL2006, - Location = {New York, New York}, - Pages = {256--263}, - Title = {Synchronous binarization for machine translation}, - Year = {2006}} - -@article{fraser07measuring, - Address = {Cambridge, MA, USA}, - Author = {Fraser, Alexander and Marcu, Daniel}, - Issn = {0891-2017}, - Journal = {Computational Linguistics}, - Number = {3}, - Pages = {293--303}, - Publisher = {MIT Press}, - Title = {Measuring Word Alignment Quality for Statistical Machine Translation}, - Volume = {33}, - Year = {2007}} - -@inproceedings{teh06, - Author = {Y. Teh}, - Booktitle = {Proc. of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics}, - Pages = {985-992}, - Title = {A Hierarchical {B}ayesian Language Model based on {P}itman-{Y}or Processes}, - Year = {2006}} - -@article{ferguson73, - Author = {S. Ferguson}, - Journal = {Annals of Statistics}, - Pages = {209--230}, - Title = {A {Bayesian} Analysis of Some Nonparametric Problems}, - Volume = 1, - Year = 1973} diff --git a/report/pyp_clustering/acl09-short/common/hyphen.sty b/report/pyp_clustering/acl09-short/common/hyphen.sty deleted file mode 100644 index 028e8fb1..00000000 --- a/report/pyp_clustering/acl09-short/common/hyphen.sty +++ /dev/null @@ -1,23 +0,0 @@ -%%%%%%%%% HYPHENATION CONTROL %%%%%%%% - -\pretolerance 250 -\tolerance 500 -% \hyphenpenalty 250 -\hyphenpenalty 200 -\exhyphenpenalty 100 -\doublehyphendemerits 7500 -\finalhyphendemerits 7500 -\brokenpenalty 10000 -\lefthyphenmin 3 -\righthyphenmin 3 -\widowpenalty 10000 -\clubpenalty 10000 -\displaywidowpenalty 10000 -\looseness 1 - -\hyphenation{phon-emic} -\hyphenation{Cam-er-oon} -\hyphenation{Kam-erun} -\hyphenation{ex-am-ple} -\hyphenation{para-digm} -\hyphenation{para-digms} diff --git a/report/pyp_clustering/acl09-short/common/jeffe.sty b/report/pyp_clustering/acl09-short/common/jeffe.sty deleted file mode 100644 index d2cd2e99..00000000 --- a/report/pyp_clustering/acl09-short/common/jeffe.sty +++ /dev/null @@ -1,566 +0,0 @@ -% ============================-*- LaTeX -*-============================= -% -% jeffe.sty -- macros I use everywhere -% -% Jeff Erickson (jeffe@cs.uiuc.edu) -% Last modified 09 Jul 2000 -% This is free; caveat emptor! -% -% Requirements that may not be part of every TeX distribution: -% (1) The standard AMS math packages amsmath and amssymb. These are -% absolutely vital to anyone who typesets mathematics of any -% kind. If you don't have them, get them NOW!! -% (2) The textcomp package. Cosmetic only. -% (3) Knuth's manual font `manfnt'. Cosmetic only. -% -% ====================================================================== -\RequirePackage{latexsym,amsmath,amssymb} - -\hyphenation{co-or-din-ate co-or-din-ates half-space stereo-iso-mers -stereo-iso-mer Round-table} - -% ---------------------------------------------------------------------- -% Common abbreviations and words with accents -% ---------------------------------------------------------------------- - -% ---- LATIN ---- -\def\etal{\emph{et~al.}} -\def\ie{\emph{i.e.}} -\def\eg{\emph{e.g.}} -\def\vitae{vit\ae{}} -\def\apriori{\emph{a~priori}} -\def\aposteriori{\emph{a~posteriori}} - -% ---- FRENCH ---- -\def\naive{na\"{\i}ve} -\def\Naive{Na\"{\i}ve} -\def\naively{na\"{\i}vely} % Okay, I know, this isn't French. -\def\Naively{Na\"{\i}vely} -\def\cafe{caf\'e} - -% ---- GERMAN ---- -\def\fur{f\"ur} -\def\Universitat{Universit\"at} -\def\Saarbrucken{Saar\-br\"ucken} % Bypass TeX hyphenation -\def\Zurich{Z\"urich} - -% ---- PORTUGESE (Hi Jorge!) ---- -\def\Computacao{Computa\c{c}\~ao} - -% ---- PROPER NAMES (because I'm lazy) ---- -\def\Benes{Bene\v{s}} % ...network -\def\Bezier{B\'ezier} % ...spline/curve/surface -\def\Bjorner{Bj\"orner} -\def\Bochis{Bochi\c{s}} % Daciana -\def\Boruvka{Bor\.uvka} % ...'s MST algorithm -\def\Bragger{Br\"agger} -\def\Bronnimann{Br\"onnimann} \def\Herve{Herv\'e} -\def\Bruckner{Br\"uckner} -\def\Caratheodory{Carath\'eodory} % Constantin -\def\Chvatal{Chv\'atal} \def\Vasek{Va\v{s}ek} - \def\Joao{Jo\~ao} % Compa -\def\Cortes{Cort\'es} % Carmen -\def\Dujmovic{Dujmovi\'c} % Vida - \def\Fredo{Fr\'edo} % Durand -\def\Erdos{Erd\H{o}s} \def\Pal{P\'al} -\def\Furedi{F\"uredi} \def\Zoltan{Zolt\'an} -\def\Grobner{Gr\"obner} % ... basis -\def\Grunbaum{Gr\"unbaum} % Branko -\def\Hanoi{Hano\"\i} % Tower of... -\def\Jarnik{Jarn\a'{\i}k} % ...'s (`Prim's') MST algorithm -\def\Komlos{Koml\'os} -\def\Kovari{K\"ov\'ari} -\def\Lovasz{Lov\'asz} \def\Laszlo{L\'aszl\'o} -\def\Matousek{Matou\v{s}ek} \def\Jiri{Ji\v{r}\'\i} -\def\Mnev{Mn\"ev} -\def\Mobius{M\"obius} % ... strip/transformation/function -\def\Mucke{M\"ucke} % Ernst -\def\ODunliang{\'O'D\'unliang} -\def\Oleinik{Ole\u{\i}nik} - \def\Janos{J\'anos} % Pach -\def\Palasti{Pal\'asti} - \def\Belen{Bel\'en} % Palop -\def\Petrovskii{Petrovski\u{\i}} -\def\Pinar{P\i nar} % Ali -\def\Plucker{Pl\"ucker} % ... coordinates -\def\Poincare{Poincar\'e} % ... duality/halfplane - \def\Gunter{G\"unter} % Rote, Ziegler -\def\Sacristan{Sacrist\'an} % Vera -\def\Saskin{\v{S}a\v{s}kin} -\def\Schomer{Sch\"omer} -\def\Schonhardt{Sch\"onhardt} % ... polyhedron -\def\Sos{S\'os} -\def\Stackel{St\"ackel} % Paul -\def\Szekely{Sz\'ekely} -\def\Szemeredi{Szemer\'edi} -\def\Toth{T\'{o}th} % Geza -\def\Turan{Tur\'an} -\def\Ungor{\"Ung\"or} % Alper -\def\Voronoi{Vorono\"i} % ... diagram [for francophile pedants only] - -% Other -\def\Cplusplus{C\raisebox{0.5ex}{\tiny\bf++}} - -% ---------------------------------------------------------------------- -% Simple math stuff -% ---------------------------------------------------------------------- - -% ---- SYMBOLS ---- -\let\e\varepsilon % a ``real'' epsilon - -\def\Integer{\mathsf{Z\hspace{-0.4em}Z}} -\def\Natural{\mathrm{I\!N}} -\def\Real{\mathrm{I\!R}} -\def\Proj{\mathrm{I\!P}} % projective space -\def\Hyper{\mathrm{I\!H}} % hyperbolic space - -% -% These two look okay in Computer Modern 11pt, or Concrete Roman -% 12pt, but they need serious work in other sizes. I need to figure -% out how to draw a vertical bar, or better yet a shallow arc, inside -% the bowls. Or maybe I need to learn METAFONT. -% -\def\Complex{\mathrm{\,\raise 0.33ex\hbox{\scriptsize\bf(}\!\!\!C}} -\def\Rational{\mathrm{\,\raise 0.33ex\hbox{\scriptsize\bf(}\!\!\!Q}} - -% -% Here are more standard, but uglier, versions of these symbols. -% They stick out, because they're all in Times Roman Bold Outline! -% I *really* want a Concrete Blackboard or Euler Blackboard font, but -% I'd settle for Computer Modern Blackboard. -% -%\def\Real{\mathbb{R}} -%\def\Proj{\mathbb{P}} -%\def\Hyper{\mathbb{H}} -%\def\Integer{\mathbb{Z}} -%\def\Natural{\mathbb{N}} -%\def\Complex{\mathbb{C}} -%\def\Rational{\mathbb{Q}} - -\let\N\Natural -\let\Q\Rational -\let\R\Real -\let\Z\Integer -\def\Rd{\Real^d} -\def\RP{\Real\Proj} -\def\CP{\Complex\Proj} - -% ---- OPERATORS (requires amsmath) ---- -\def\aff{\operatorname{aff}} % (\Line is better!) -\def\area{\operatorname{area}} -\def\argmax{\operatornamewithlimits{arg\,max}} -\def\argmin{\operatornamewithlimits{arg\,min}} -\def\Aut{\operatorname{Aut}} % Automorphism group -\def\card{\operatorname{card}} % cardinality, deprecated for \abs -\def\conv{\operatorname{conv}} % (\overline is better!) -\def\E{\operatorname{E}} % Expectation: $\E[X]$ (like \Pr) -\def\EE{\operatornamewithlimits{E}} -\def\Hom{\operatorname{Hom}} % Homomorphism group -\def\id{\operatorname{id}} % identity -\def\im{\operatorname{im}} % image -\def\lcm{\operatorname{lcm}} -\def\lfs{\operatorname{lfs}} % local feature size -\def\poly{\operatorname{poly}} -\def\polylog{\operatorname{polylog}} -\def\rank{\operatorname{rank}} -\def\rel{\operatorname{rel\,}} % relative (interior, boundary, etc.) -\def\sgn{\operatorname{sgn}} -\def\vol{\operatorname{vol}} % volume - -\def\fp#1{^{\underline{#1}}} % falling powers: $n\fp{d}$ -\def\rp#1{^{\overline{#1}}} % rising powers: $n\rp{d}$ - -% --- Cheap displaystyle operators --- -\def\Frac#1#2{{\displaystyle\frac{#1}{#2}}} -\def\Sum{\sum\limits} -\def\Prod{\prod\limits} -\def\Union{\bigcup\limits} -\def\Inter{\bigcap\limits} -\def\Lor{\bigvee\limits} -\def\Land{\bigwedge\limits} -\def\Lim{\lim\limits} -\def\Max{\max\limits} -\def\Min{\min\limits} - -% ---- RELATORS ---- -\def\deq{\stackrel{\scriptscriptstyle\triangle}{=}} -\def\mapsfrom{\leftarrow\!\mapstochar\,} -\let\into\hookrightarrow % = one-to-one -\let\onto\twoheadrightarrow - -% ---- DELIMITER PAIRS ---- -\def\floor#1{\lfloor #1 \rfloor} -\def\ceil#1{\lceil #1 \rceil} -\def\seq#1{\langle #1 \rangle} -\def\set#1{\{ #1 \}} -\def\abs#1{\mathopen| #1 \mathclose|} % use instead of $|x|$ -\def\norm#1{\mathopen\| #1 \mathclose\|}% use instead of $\|x\|$ -\def\indic#1{\big[#1\big]} % indicator variable; Iverson notation - % e.g., Kronecker delta = [x=0] - -% --- Self-scaling delmiter pairs --- -\def\Floor#1{\left\lfloor #1 \right\rfloor} -\def\Ceil#1{\left\lceil #1 \right\rceil} -\def\Seq#1{\left\langle #1 \right\rangle} -\def\Set#1{\left\{ #1 \right\}} -\def\Abs#1{\left| #1 \right|} -\def\Norm#1{\left\| #1 \right\|} -\def\Paren#1{\left( #1 \right)} % need better macro name! -\def\Brack#1{\left[ #1 \right]} % need better macro name! -\def\Indic#1{\left[ #1 \right]} % indicator variable; Iverson notation - -% -% Macros to typeset sets like {foo|bar} with all three delimiters -% correctly scaled to fit. What I *really* want is a \middle macro -% that acts just like \left and \right. Grumble. -% -\def\Bigbar#1{\mathrel{\left|\vphantom{#1}\right.\n@space}} -\def\Setbar#1#2{\Set{#1 \Bigbar{#1 #2} #2}} -\def\Seqbar#1#2{\Seq{#1 \Bigbar{#1 #2} #2}} -\def\Brackbar#1#2{\Brack{#1 \Bigbar{#1 #2} #2}} - -% C-style arithmetic if-then-else -\def\arithif#1#2#3{#1 \mathbin? #2 \mathbin: #3} - -% Math mode fbox -\def\mfbox#1{\mathchoice{{\fbox{\ensuremath{\displaystyle #1}}}} - {{\fbox{\ensuremath{\textstyle #1}}}} - {{\fbox{\ensuremath{\scriptstyle #1}}}} - {{\fbox{\ensuremath{\scriptscriptstyle #1}}}}} - -% ---- ``ACCENTS'' ---- -% NB: Commands equivalent to \lrarrowfill and \overlrarrow are -% already defined in amstex! -\def\lrarrowfill{$\m@th\mathord\leftarrow\mkern-6mu% - \cleaders\hbox{$\mkern-2mu\mathord-\mkern-2mu$}\hfill - \mkern-6mu\mathord\rightarrow$} -\def\overlrarrow#1{\vbox{\ialign{##\crcr - \lrarrowfill\crcr\noalign{\kern-\p@\nointerlineskip} - $\hfil\displaystyle{#1}\hfil$\crcr}}} - -\def\Line#1{\!\overlrarrow{\vphantom{t}\smash{\,#1\,}}\!} -\def\Ray#1{\overrightarrow{\vphantom{t}#1\,}\!} -\def\Seg#1{\overline{\vphantom{t}#1}} - -% --- TEXT STYLES --- -\def\mathsc#1{\text{\textsc{#1}}} -\def\mathbs#1{\text{\boldmath\ensuremath{#1}}} - -% ---------------------------------------------------------------------- -% \begin{bigabstract}...\end{bigabstract} -% For use in documents with title pages. Use normal-sized text in -% the abstract! -% ---------------------------------------------------------------------- -\newenvironment{bigabstract}% -{\medskip\noindent\centerline{\textbf{\large\abstractname}}\begin{quotation}}% -{\end{quotation}} - -% ---------------------------------------------------------------------- -% Make captions smaller than the text, make their titles bold. -% Arguments: #1 == figure name: "Figure 5" -% #2 == caption: "Papers by \Erdos, 1900--2000 (projected)" -% Less space after floats and before caption, since captions are smaller -% ---------------------------------------------------------------------- -\@ifundefined{abovecaptionskip}{\newlength\abovecaptionskip} -\long\def\@makecaption#1#2{ - \vskip \abovecaptionskip - \setbox\@tempboxa\hbox{{\sf\footnotesize \textbf{#1.} #2}} - \ifdim \wd\@tempboxa >\hsize % IF longer than one line: - {\sf\footnotesize \textbf{#1.} #2\par}% THEN set as ordinary paragraph. - \else % ELSE center. - \hbox to\hsize{\hfil\box\@tempboxa\hfil} - \fi} -\dbltextfloatsep 18pt plus 2pt minus 4pt% was 20pt plus 2pt minus 4pt -\textfloatsep 18pt plus 2pt minus 4pt % was 20pt plus 2pt minus 4pt -\abovecaptionskip 6pt % was 10pt - -% ---------------------------------------------------------------------- -% Revised theorem environment: -% Add a period after the theorem number, and make theorems slanted -% instead of italic to help distinguish text from math. Use -% \boldmath in theorem label in case it includes math. -% ---------------------------------------------------------------------- -\def\@opargbegintheorem#1#2#3{\trivlist - \item[\hskip\labelsep{\bf\boldmath #1\ #2\ (#3).}]\sl} -\def\@begintheorem#1#2{\trivlist - \item[\hskip\labelsep{\bf\boldmath #1\ #2.}]\sl} - -% ---------------------------------------------------------------------- -% \newproof{type}{text}(style)[post]: -% Define a new type of unnumbered ``theorem'' environment. The last -% two arguments are optional; most environments will not use them. -% -% To change label style, put new style command in label: -% \newproof{comment}{\sf Comment} -% ---------------------------------------------------------------------- -\def\newproof#1#2{\@ifnextchar({\@snproof{#1}{#2}}{\@snproof{#1}{#2}(\rm)}} -\def\@snproof#1#2(#3){\@ifnextchar[{\@xnproof{#1}{#2}{#3}} - {\@xnproof{#1}{#2}{#3}[]}} - -\def\@xnproof#1#2#3[#4]{%\expandafter\@ifdefinable\csname #1\endcsname -{\global\@namedef{#1}{\@prf{#2}{#3}}\global\@namedef{end#1}{\@endprf{#4}}}} - -\def\@prf#1#2{\@ifnextchar[{\@xprf{#1}{#2}}{\@yprf{#1}{#2}}} -\def\@xprf#1#2[#3]{\@yprf{#1\ (#3)}{#2}} -\def\@yprf#1#2{\begin{trivlist}\item[\hskip\labelsep{\bf\boldmath #1:}]#2} - -\def\@endprf#1{#1\end{trivlist}} - -% -% Standard proof envrionment: last line has a halmos at the right margin. -% -\@ifundefined{square}{\let\square\Box}{} % grumble latex2e -\def\QED{\ensuremath{{\square}}} -\def\markatright#1{\leavevmode\unskip\nobreak\quad\hspace*{\fill}{#1}} -\def\qed{\markatright{\QED}} -\newproof{proof}{Proof}[\qed] -\newproof{sketch}{Proof Sketch}[\qed] - -\newenvironment{rawproof}% - {\begin{trivlist}\item[\hskip\labelsep\textbf{Proof:}]}% - {\qed\end{trivlist}} - -% -% If the proof ends with a displayed equation, use \aftermath just -% before \end{proof} to put the halmos in the ``right'' place. This -% may not work near page boundaries. -% -\def\aftermath{\par\vspace{-\belowdisplayskip}\vspace{-\parskip}\vspace{-\baselineskip}} - -% ---------------------------------------------------------------------- -% One-shot theoremish environment. For named things like ``Zorn's -% Lemma'' or ``The Death Leap Principle'' or ``The Zone Theorem''. -% To get one-shot proofish environment, put \rm inside. -% New improved version stolen from Erik Demaine. -% ---------------------------------------------------------------------- -\newenvironment{oneshot}[1]{\@begintheorem{#1}{\unskip}}{\@endtheorem} - -% ---------------------------------------------------------------------- -% Algorithm and code environments -- Algorithms are set in normal -% text, with 2em indenting, surrounded by a box. Code is set in -% typewriter text, with 4 space indenting, and no box. -% -% NOTE! The true width of the minipage environment is determined by -% the contents of the longest line, but ONLY because the minipage -% contains a tabbing environment, and nothing else. It's a HaX! -% -% Both environments need optional line numbering and comment macros, -% but bold keywords are just distracting. -% ---------------------------------------------------------------------- -\def\begin@lgo{\begin{minipage}{1in}\begin{tabbing} - \quad\=\qquad\=\qquad\=\qquad\=\qquad\=\qquad\=\qquad\=\kill} -\def\end@lgo{\end{tabbing}\end{minipage}} - -\newenvironment{algorithm} -{\begin{tabular}{|l|}\hline\begin@lgo} -{\end@lgo\\\hline\end{tabular}} - -\newenvironment{algo} -{\begin{center}\begin{algorithm}} -{\end{algorithm}\end{center}} - -\def\Comment#1{\textsf{\textsl{$\langle\!\langle$#1\/$\rangle\!\rangle$}}} - -\def\beginc@de{\noindent\begin{center}\begin{minipage}{1in}\tt - \begin{tabbing}~~~~\=~~~~\=~~~~\=~~~~\=~~~~\=~~~~\=~~~~\=\kill} -\def\endc@de{\end{tabbing}\end{minipage}\end{center}} - -\newenvironment{code}{\beginc@de}{\endc@de} - -% -% I think these only work with <1 line of text. Use sparingly!! -% -\def\textul#1{\underline{\smash{#1}\vphantom{,}}} -\def\strike#1{\ensuremath{\overline{\text{\smash{#1}\vphantom{.}}}}} - -% ---------------------------------------------------------------------- -% Include a file verbatim. Searches the TEXINPUTS path for the file, -% even though that's probably not what you really want. Stolen from -% ``verbatimfiles.sty'' by Chris Rowley and others. [Don't use their -% \vertbatimlisting macro; it has some bizarre side-effects!] -% ---------------------------------------------------------------------- -\def\verbinput#1{ -\begingroup\@verbatim\frenchspacing\@vobeyspaces\input#1\endgroup -} - -% ---------------------------------------------------------------------- -% \now -- Current time in h:mm AM/PM format -% \mdyy -- Today's date in m/d/yy format. Forget Y2K; this is for humans! -% ---------------------------------------------------------------------- -\newcount\timehh\timehh=\time -\divide\timehh by 60 -\newcount\timemm\timemm=\time -\count255=\timehh -\multiply\count255 by -60 -\advance\timemm by \count255 -\newif\iftimePM -\ifnum\timehh>11 \timePMtrue\else\timePMfalse\fi -\ifnum\timehh<1 \advance\timehh by 12\fi -\ifnum\timehh>12 \advance\timehh by -12\fi -\def\now{\number\timehh:\ifnum\timemm<10 0\fi\number\timemm - \iftimePM pm\else am\fi} -\newcount\mdYY\mdYY=\year -\count255=\year -\divide\count255 by 100 -\multiply\count255 by 100 -\advance\mdYY by -\count255 -\def\mdyy{\number\month/\number\day/\ifnum\mdYY<10 0\fi\number\mdYY} - -% ---------------------------------------------------------------------- -% Notes to myself -% ---------------------------------------------------------------------- -\def\n@te#1{\textsf{$\langle\!\langle$#1$\rangle\!\rangle$}\leavevmode} -\def\n@tew@rn{\GenericWarning{}{AUTHOR WARNING: Unresolved \protect\note}} - -\def\n@ten@te#1{\marginpar - [\hfill\llap{\textcircled{\small#1}$\!\Longrightarrow$}] - {\rlap{$\Longleftarrow\!$\textcircled{\small#1}}}} - -\def\n@tedingb@t{\@ifundefined{textmusicalnote} - {$\circledcirc$} % if you don't have textcomp - {\textmusicalnote}} % if you do have textcomp - -\def\note#1{\n@tew@rn\n@te{\n@ten@te{\n@tedingb@t}#1}} - -\def\sidenote#1{\marginpar{\tiny\sf #1}} - - -%---------------------------------------------------------------------- -% Bibliography aliases, so I can use mnemonic citation keys and -% geom.bib at the same time. \bibalias{foo}{bar} makes \cite{foo} -% act (almost) exactly like \cite{bar}. -%---------------------------------------------------------------------- -\def\bibalias#1#2{% - \global\@namedef{b@#1}{% - {\@ifundefined{b@#2}{\textsf{?}}{}\csname b@#2\endcsname}}} - -%---------------------------------------------------------------------- -% Flag bad citations and refernces in the margin. Dangerous if you -% have lots of undefined refs; use batchmode the first time. -% Incompatible with some document classes. -%---------------------------------------------------------------------- -\DeclareOption{flagerrors} -{ -\def\badcite{\ifinner\else\n@ten@te{\textcent}\fi} - -\def\badref{\ifinner\else\n@ten@te{$\Join$}\fi} - -\def\bibalias#1#2{% - \global\@namedef{b@#1}{% - {\@ifundefined{b@#2}{\textsf{>>#1??}}{}\csname b@#2\endcsname}}} - -\def\@citex[#1]#2{% - \let\@citea\@empty - \@cite{\@for\@citeb:=#2\do - {\@citea\def\@citea{,\penalty\@m\ }% - \edef\@citeb{\expandafter\@firstofone\@citeb\@empty}% - \if@filesw\immediate\write\@auxout{\string\citation{\@citeb}}\fi - \@ifundefined{b@\@citeb}{\mbox{\reset@font\sffamily>\@citeb?}% - \badcite% - \G@refundefinedtrue% - \@latex@warning - {Citation `\@citeb' on page \thepage \space undefined}}% - {\hbox{\csname b@\@citeb\endcsname}}}}{#1}} - -\def\@setref#1#2#3{ - \ifx#1\relax - \protect\G@refundefinedtrue - \badref\mbox{\reset@font\sffamily >#3?} - \@latex@warning{Reference `#3' on page \thepage \space undefined}% - \else - \expandafter#2#1\null - \fi} -} - - -% ---------------------------------------------------------------------- -% Draft notice. Put \DRAFT on the title page, in place of \date. -% ---------------------------------------------------------------------- -\def\draftnotice{Preliminary draft --- \mdyy\ --- Not for distribution} - -\def\DRAFT{ -\date{\fbox{\textsf{\textbf{\draftnotice}}}} -\def\@oddfoot{\footnotesize\hss\fbox{\textbf{\textsf{\draftnotice}}}\hss} -\let\@evenfoot\@oddfoot -} - -% ---------------------------------------------------------------------- -% Dingbats from the TeX/METAFONT-book manual font -% Use only with 11 or 12 pt text. -% Doesn't work with TeXtures, which doesn't know about manfnt. -% ---------------------------------------------------------------------- -\font\manual=manfnt -\def\goodcube{{\manual\char28}} % possible cube from MF-book -\def\badcube{{\manual\char29}} % impossible cube from MF-book -\def\starknot{{\manual\char30}} % 2,5 torus knot from MF-book -\def\target{{\manual\char36}} % concentric circles from MF-book -\def\xflower{{\manual\char38}} % X flower dingbat from MF-book -\def\tflower{{\manual\char39}} % + flower dingbat from MF-book -\def\changeto{{\manual\char121}}% change arrow -\def\dbend{{\manual\char127}} % dangerous bend sign - -% ---------------------------------------------------------------------- -% Dangerous bend environments, stolen from TeXbook and slightly -% massaged. -% -% Invoke as \begin{[d]danger}...\end{[d]danger}. The enclosed text -% is offset just like any other list (theorem, proof, etc.) Puts -% sign[s] in front of first two lines of first paragraph, which are -% (supposedly) never split by a page boundary. Does NOT shrink or -% otherwise modify the text. -% ---------------------------------------------------------------------- -% The dangerous bend signs are the correct size to match two lines of -% Computer Modern 9pt type. I really ought to scale them up to -% fit whatever size we're using, but I won't. Unfortunately, manfnt -% thinks it's a 10pt font, so if we want to match 11pt Computer -% Modern, we have to scale manfnt to 12.222222pt! Thanks, Don. -% -% TeX is a HaX. -% ---------------------------------------------------------------------- - -% Single danger -\def\danger{\begin{trivlist}\item[]\noindent% -\begingroup\hangindent=2.5pc\hangafter=-2\clubpenalty=10000% -\def\par{\endgraf\endgroup}% -\hbox to 0pt{\hskip-\hangindent\dbend\hfill}\ignorespaces} -\def\enddanger{\end{trivlist}} - -% Double danger -\def\ddanger{\begin{trivlist}\item[]\noindent% -\begingroup\hangindent=4pc\hangafter=-2\clubpenalty=10000% -\def\par{\endgraf\endgroup}% -\hbox to 0pt{\hskip-\hangindent\dbend\kern2pt\dbend\hfill}\ignorespaces} -\def\endddanger{\end{trivlist}} - -%---------------------------------------------------------------------- -% 'cramped' list style, stolen from Jeff Vitter -%---------------------------------------------------------------------- -\def\cramped - {\parskip\@outerparskip\@topsep\parskip - \@topsepadd2pt\itemsep0pt -% \settowidth{\labelwidth}{\@itemlabel} -% \advance\leftmargin-\labelsep -% \advance\leftmargin-\labelwidth -% \advance\@totalleftmargin-\leftmargin -% \advance\linewidth\leftmargin -% \parshape1\@totalleftmargin\linewidth -} - -%---------------------------------------------------------------------- -% More footnote symbols, please. -%---------------------------------------------------------------------- -\def\@fnsymbol#1{\ensuremath{\ifcase#1\or *\or \dagger\or \ddagger\or - \mathsection\or \mathparagraph\or \|\or **\or \dagger\dagger - \or \ddagger\ddagger \or \mathsection\mathsection \or - \mathparagraph\mathparagraph \else\@ctrerr\fi}} - -%---------------------------------------------------------------------- -% TeXbook style quotations -- I should really use the right font, tho. -%---------------------------------------------------------------------- -\newenvironment{rightquote}[1] -{\flushright\begin{minipage}{#1\textwidth} -\parskip0pt\footnotesize\sffamily\slshape} -{\end{minipage}\par\bigskip} -\def\quotee#1{\par\vspace{0.5ex}\flushright\unskip\textup{--- #1}} - -\ProcessOptions diff --git a/report/pyp_clustering/acl09-short/common/naaclhlt2010.bst b/report/pyp_clustering/acl09-short/common/naaclhlt2010.bst deleted file mode 100644 index 4396d4dc..00000000 --- a/report/pyp_clustering/acl09-short/common/naaclhlt2010.bst +++ /dev/null @@ -1,1322 +0,0 @@ - -% BibTeX `acl' style file for BibTeX version 0.99c, LaTeX version 2.09 -% This version was made by modifying `aaai-named' format based on the master -% file by Oren Patashnik (PATASHNIK@SCORE.STANFORD.EDU) - -% Copyright (C) 1985, all rights reserved. -% Modifications Copyright 1988, Peter F. Patel-Schneider -% Further modifictions by Stuart Shieber, 1991, and Fernando Pereira, 1992. -% Copying of this file is authorized only if either -% (1) you make absolutely no changes to your copy, including name, or -% (2) if you do make changes, you name it something other than -% btxbst.doc, plain.bst, unsrt.bst, alpha.bst, and abbrv.bst. -% This restriction helps ensure that all standard styles are identical. - -% There are undoubtably bugs in this style. If you make bug fixes, -% improvements, etc. please let me know. My e-mail address is: -% pfps@spar.slb.com - -% Citation format: [author-last-name, year] -% [author-last-name and author-last-name, year] -% [author-last-name {\em et al.}, year] -% -% Reference list ordering: alphabetical by author or whatever passes -% for author in the absence of one. -% -% This BibTeX style has support for short (year only) citations. This -% is done by having the citations actually look like -% \citename{name-info, }year -% The LaTeX style has to have the following -% \let\@internalcite\cite -% \def\cite{\def\citename##1{##1}\@internalcite} -% \def\shortcite{\def\citename##1{}\@internalcite} -% \def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} -% which makes \shortcite the macro for short citations. - -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% -% Changes made by SMS for thesis style -% no emphasis on "et al." -% "Ph.D." includes periods (not "PhD") -% moved year to immediately after author's name -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% -ENTRY - { address - author - booktitle - chapter - edition - editor - howpublished - institution - journal - key - month - note - number - organization - pages - publisher - school - series - title - type - volume - year - } - {} - { label extra.label sort.label } - -INTEGERS { output.state before.all mid.sentence after.sentence after.block } - -FUNCTION {init.state.consts} -{ #0 'before.all := - #1 'mid.sentence := - #2 'after.sentence := - #3 'after.block := -} - -STRINGS { s t } - -FUNCTION {output.nonnull} -{ 's := - output.state mid.sentence = - { ", " * write$ } - { output.state after.block = - { add.period$ write$ - newline$ - "\newblock " write$ - } - { output.state before.all = - 'write$ - { add.period$ " " * write$ } - if$ - } - if$ - mid.sentence 'output.state := - } - if$ - s -} - -FUNCTION {output} -{ duplicate$ empty$ - 'pop$ - 'output.nonnull - if$ -} - -FUNCTION {output.check} -{ 't := - duplicate$ empty$ - { pop$ "empty " t * " in " * cite$ * warning$ } - 'output.nonnull - if$ -} - -FUNCTION {output.bibitem} -{ newline$ - - "\bibitem[" write$ - label write$ - "]{" write$ - - cite$ write$ - "}" write$ - newline$ - "" - before.all 'output.state := -} - -FUNCTION {fin.entry} -{ add.period$ - write$ - newline$ -} - -FUNCTION {new.block} -{ output.state before.all = - 'skip$ - { after.block 'output.state := } - if$ -} - -FUNCTION {new.sentence} -{ output.state after.block = - 'skip$ - { output.state before.all = - 'skip$ - { after.sentence 'output.state := } - if$ - } - if$ -} - -FUNCTION {not} -{ { #0 } - { #1 } - if$ -} - -FUNCTION {and} -{ 'skip$ - { pop$ #0 } - if$ -} - -FUNCTION {or} -{ { pop$ #1 } - 'skip$ - if$ -} - -FUNCTION {new.block.checka} -{ empty$ - 'skip$ - 'new.block - if$ -} - -FUNCTION {new.block.checkb} -{ empty$ - swap$ empty$ - and - 'skip$ - 'new.block - if$ -} - -FUNCTION {new.sentence.checka} -{ empty$ - 'skip$ - 'new.sentence - if$ -} - -FUNCTION {new.sentence.checkb} -{ empty$ - swap$ empty$ - and - 'skip$ - 'new.sentence - if$ -} - -FUNCTION {field.or.null} -{ duplicate$ empty$ - { pop$ "" } - 'skip$ - if$ -} - -FUNCTION {emphasize} -{ duplicate$ empty$ - { pop$ "" } - { "{\em " swap$ * "}" * } - if$ -} - -INTEGERS { nameptr namesleft numnames } - -FUNCTION {format.names} -{ 's := - #1 'nameptr := - s num.names$ 'numnames := - numnames 'namesleft := - { namesleft #0 > } - - { s nameptr "{ff~}{vv~}{ll}{, jj}" format.name$ 't := - - nameptr #1 > - { namesleft #1 > - { ", " * t * } - { numnames #2 > - { "," * } - 'skip$ - if$ - t "others" = - { " et~al." * } - { " and " * t * } - if$ - } - if$ - } - 't - if$ - nameptr #1 + 'nameptr := - namesleft #1 - 'namesleft := - } - while$ -} - -FUNCTION {format.authors} -{ author empty$ - { "" } - { author format.names } - if$ -} - -FUNCTION {format.editors} -{ editor empty$ - { "" } - { editor format.names - editor num.names$ #1 > - { ", editors" * } - { ", editor" * } - if$ - } - if$ -} - -FUNCTION {format.title} -{ title empty$ - { "" } - - { title "t" change.case$ } - - if$ -} - -FUNCTION {n.dashify} -{ 't := - "" - { t empty$ not } - { t #1 #1 substring$ "-" = - { t #1 #2 substring$ "--" = not - { "--" * - t #2 global.max$ substring$ 't := - } - { { t #1 #1 substring$ "-" = } - { "-" * - t #2 global.max$ substring$ 't := - } - while$ - } - if$ - } - { t #1 #1 substring$ * - t #2 global.max$ substring$ 't := - } - if$ - } - while$ -} - -FUNCTION {format.date} -{ year empty$ - { month empty$ - { "" } - { "there's a month but no year in " cite$ * warning$ - month - } - if$ - } - { month empty$ - { "" } - { month } - if$ - } - if$ -} - -FUNCTION {format.btitle} -{ title emphasize -} - -FUNCTION {tie.or.space.connect} -{ duplicate$ text.length$ #3 < - { "~" } - { " " } - if$ - swap$ * * -} - -FUNCTION {either.or.check} -{ empty$ - 'pop$ - { "can't use both " swap$ * " fields in " * cite$ * warning$ } - if$ -} - -FUNCTION {format.bvolume} -{ volume empty$ - { "" } - { "volume" volume tie.or.space.connect - series empty$ - 'skip$ - { " of " * series emphasize * } - if$ - "volume and number" number either.or.check - } - if$ -} - -FUNCTION {format.number.series} -{ volume empty$ - { number empty$ - { series field.or.null } - { output.state mid.sentence = - { "number" } - { "Number" } - if$ - number tie.or.space.connect - series empty$ - { "there's a number but no series in " cite$ * warning$ } - { " in " * series * } - if$ - } - if$ - } - { "" } - if$ -} - -FUNCTION {format.edition} -{ edition empty$ - { "" } - { output.state mid.sentence = - { edition "l" change.case$ " edition" * } - { edition "t" change.case$ " edition" * } - if$ - } - if$ -} - -INTEGERS { multiresult } - -FUNCTION {multi.page.check} -{ 't := - #0 'multiresult := - { multiresult not - t empty$ not - and - } - { t #1 #1 substring$ - duplicate$ "-" = - swap$ duplicate$ "," = - swap$ "+" = - or or - { #1 'multiresult := } - { t #2 global.max$ substring$ 't := } - if$ - } - while$ - multiresult -} - -FUNCTION {format.pages} -{ pages empty$ - { "" } - { pages multi.page.check - { "pages" pages n.dashify tie.or.space.connect } - { "page" pages tie.or.space.connect } - if$ - } - if$ -} - -FUNCTION {format.year.label} -{ year extra.label * -} - -FUNCTION {format.vol.num.pages} -{ volume field.or.null - number empty$ - 'skip$ - { "(" number * ")" * * - volume empty$ - { "there's a number but no volume in " cite$ * warning$ } - 'skip$ - if$ - } - if$ - pages empty$ - 'skip$ - { duplicate$ empty$ - { pop$ format.pages } - { ":" * pages n.dashify * } - if$ - } - if$ -} - -FUNCTION {format.chapter.pages} -{ chapter empty$ - 'format.pages - { type empty$ - { "chapter" } - { type "l" change.case$ } - if$ - chapter tie.or.space.connect - pages empty$ - 'skip$ - { ", " * format.pages * } - if$ - } - if$ -} - -FUNCTION {format.in.ed.booktitle} -{ booktitle empty$ - { "" } - { editor empty$ - { "In " booktitle emphasize * } - { "In " format.editors * ", " * booktitle emphasize * } - if$ - } - if$ -} - -FUNCTION {empty.misc.check} -{ author empty$ title empty$ howpublished empty$ - month empty$ year empty$ note empty$ - and and and and and - - key empty$ not and - - { "all relevant fields are empty in " cite$ * warning$ } - 'skip$ - if$ -} - -FUNCTION {format.thesis.type} -{ type empty$ - 'skip$ - { pop$ - type "t" change.case$ - } - if$ -} - -FUNCTION {format.tr.number} -{ type empty$ - { "Technical Report" } - 'type - if$ - number empty$ - { "t" change.case$ } - { number tie.or.space.connect } - if$ -} - -FUNCTION {format.article.crossref} -{ key empty$ - { journal empty$ - { "need key or journal for " cite$ * " to crossref " * crossref * - warning$ - "" - } - { "In {\em " journal * "\/}" * } - if$ - } - { "In " key * } - if$ - " \cite{" * crossref * "}" * -} - -FUNCTION {format.crossref.editor} -{ editor #1 "{vv~}{ll}" format.name$ - editor num.names$ duplicate$ - #2 > - { pop$ " et~al." * } - { #2 < - 'skip$ - { editor #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" = - { " et~al." * } - { " and " * editor #2 "{vv~}{ll}" format.name$ * } - if$ - } - if$ - } - if$ -} - -FUNCTION {format.book.crossref} -{ volume empty$ - { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ - "In " - } - { "Volume" volume tie.or.space.connect - " of " * - } - if$ - editor empty$ - editor field.or.null author field.or.null = - or - { key empty$ - { series empty$ - { "need editor, key, or series for " cite$ * " to crossref " * - crossref * warning$ - "" * - } - { "{\em " * series * "\/}" * } - if$ - } - { key * } - if$ - } - { format.crossref.editor * } - if$ - " \cite{" * crossref * "}" * -} - -FUNCTION {format.incoll.inproc.crossref} -{ editor empty$ - editor field.or.null author field.or.null = - or - { key empty$ - { booktitle empty$ - { "need editor, key, or booktitle for " cite$ * " to crossref " * - crossref * warning$ - "" - } - { "In {\em " booktitle * "\/}" * } - if$ - } - { "In " key * } - if$ - } - { "In " format.crossref.editor * } - if$ - " \cite{" * crossref * "}" * -} - -FUNCTION {article} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - crossref missing$ - { journal emphasize "journal" output.check - format.vol.num.pages output - format.date output - } - { format.article.crossref output.nonnull - format.pages output - } - if$ - new.block - note output - fin.entry -} - -FUNCTION {book} -{ output.bibitem - author empty$ - { format.editors "author and editor" output.check } - { format.authors output.nonnull - crossref missing$ - { "author and editor" editor either.or.check } - 'skip$ - if$ - } - if$ - new.block - format.year.label "year" output.check - new.block - format.btitle "title" output.check - crossref missing$ - { format.bvolume output - new.block - format.number.series output - new.sentence - publisher "publisher" output.check - address output - } - { new.block - format.book.crossref output.nonnull - } - if$ - format.edition output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {booklet} -{ output.bibitem - format.authors output - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - howpublished address new.block.checkb - howpublished output - address output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {inbook} -{ output.bibitem - author empty$ - { format.editors "author and editor" output.check } - { format.authors output.nonnull - crossref missing$ - { "author and editor" editor either.or.check } - 'skip$ - if$ - } - if$ - format.year.label "year" output.check - new.block - new.block - format.btitle "title" output.check - crossref missing$ - { format.bvolume output - format.chapter.pages "chapter and pages" output.check - new.block - format.number.series output - new.sentence - publisher "publisher" output.check - address output - } - { format.chapter.pages "chapter and pages" output.check - new.block - format.book.crossref output.nonnull - } - if$ - format.edition output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {incollection} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - crossref missing$ - { format.in.ed.booktitle "booktitle" output.check - format.bvolume output - format.number.series output - format.chapter.pages output - new.sentence - publisher "publisher" output.check - address output - format.edition output - format.date output - } - { format.incoll.inproc.crossref output.nonnull - format.chapter.pages output - } - if$ - new.block - note output - fin.entry -} - -FUNCTION {inproceedings} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - crossref missing$ - { format.in.ed.booktitle "booktitle" output.check - format.bvolume output - format.number.series output - format.pages output - address empty$ - { organization publisher new.sentence.checkb - organization output - publisher output - format.date output - } - { address output.nonnull - format.date output - new.sentence - organization output - publisher output - } - if$ - } - { format.incoll.inproc.crossref output.nonnull - format.pages output - } - if$ - new.block - note output - fin.entry -} - -FUNCTION {conference} { inproceedings } - -FUNCTION {manual} -{ output.bibitem - author empty$ - { organization empty$ - 'skip$ - { organization output.nonnull - address output - } - if$ - } - { format.authors output.nonnull } - if$ - format.year.label "year" output.check - new.block - new.block - format.btitle "title" output.check - author empty$ - { organization empty$ - { address new.block.checka - address output - } - 'skip$ - if$ - } - { organization address new.block.checkb - organization output - address output - } - if$ - format.edition output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {mastersthesis} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - "Master's thesis" format.thesis.type output.nonnull - school "school" output.check - address output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {misc} -{ output.bibitem - format.authors output - new.block - format.year.label output - new.block - title howpublished new.block.checkb - format.title output - howpublished new.block.checka - howpublished output - format.date output - new.block - note output - fin.entry - empty.misc.check -} - -FUNCTION {phdthesis} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.btitle "title" output.check - new.block - "{Ph.D.} thesis" format.thesis.type output.nonnull - school "school" output.check - address output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {proceedings} -{ output.bibitem - editor empty$ - { organization output } - { format.editors output.nonnull } - if$ - new.block - format.year.label "year" output.check - new.block - format.btitle "title" output.check - format.bvolume output - format.number.series output - address empty$ - { editor empty$ - { publisher new.sentence.checka } - { organization publisher new.sentence.checkb - organization output - } - if$ - publisher output - format.date output - } - { address output.nonnull - format.date output - new.sentence - editor empty$ - 'skip$ - { organization output } - if$ - publisher output - } - if$ - new.block - note output - fin.entry -} - -FUNCTION {techreport} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - format.tr.number output.nonnull - institution "institution" output.check - address output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {unpublished} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - note "note" output.check - format.date output - fin.entry -} - -FUNCTION {default.type} { misc } - -MACRO {jan} {"January"} - -MACRO {feb} {"February"} - -MACRO {mar} {"March"} - -MACRO {apr} {"April"} - -MACRO {may} {"May"} - -MACRO {jun} {"June"} - -MACRO {jul} {"July"} - -MACRO {aug} {"August"} - -MACRO {sep} {"September"} - -MACRO {oct} {"October"} - -MACRO {nov} {"November"} - -MACRO {dec} {"December"} - -MACRO {acmcs} {"ACM Computing Surveys"} - -MACRO {acta} {"Acta Informatica"} - -MACRO {cacm} {"Communications of the ACM"} - -MACRO {ibmjrd} {"IBM Journal of Research and Development"} - -MACRO {ibmsj} {"IBM Systems Journal"} - -MACRO {ieeese} {"IEEE Transactions on Software Engineering"} - -MACRO {ieeetc} {"IEEE Transactions on Computers"} - -MACRO {ieeetcad} - {"IEEE Transactions on Computer-Aided Design of Integrated Circuits"} - -MACRO {ipl} {"Information Processing Letters"} - -MACRO {jacm} {"Journal of the ACM"} - -MACRO {jcss} {"Journal of Computer and System Sciences"} - -MACRO {scp} {"Science of Computer Programming"} - -MACRO {sicomp} {"SIAM Journal on Computing"} - -MACRO {tocs} {"ACM Transactions on Computer Systems"} - -MACRO {tods} {"ACM Transactions on Database Systems"} - -MACRO {tog} {"ACM Transactions on Graphics"} - -MACRO {toms} {"ACM Transactions on Mathematical Software"} - -MACRO {toois} {"ACM Transactions on Office Information Systems"} - -MACRO {toplas} {"ACM Transactions on Programming Languages and Systems"} - -MACRO {tcs} {"Theoretical Computer Science"} - -READ - -FUNCTION {sortify} -{ purify$ - "l" change.case$ -} - -INTEGERS { len } - -FUNCTION {chop.word} -{ 's := - 'len := - s #1 len substring$ = - { s len #1 + global.max$ substring$ } - 's - if$ -} - -INTEGERS { et.al.char.used } - -FUNCTION {initialize.et.al.char.used} -{ #0 'et.al.char.used := -} - -EXECUTE {initialize.et.al.char.used} - -FUNCTION {format.lab.names} -{ 's := - s num.names$ 'numnames := - - numnames #1 = - { s #1 "{vv }{ll}" format.name$ } - { numnames #2 = - { s #1 "{vv }{ll }and " format.name$ s #2 "{vv }{ll}" format.name$ * - } - { s #1 "{vv }{ll }\bgroup et al.\egroup " format.name$ } - if$ - } - if$ - -} - -FUNCTION {author.key.label} -{ author empty$ - { key empty$ - - { cite$ #1 #3 substring$ } - - { key #3 text.prefix$ } - if$ - } - { author format.lab.names } - if$ -} - -FUNCTION {author.editor.key.label} -{ author empty$ - { editor empty$ - { key empty$ - - { cite$ #1 #3 substring$ } - - { key #3 text.prefix$ } - if$ - } - { editor format.lab.names } - if$ - } - { author format.lab.names } - if$ -} - -FUNCTION {author.key.organization.label} -{ author empty$ - { key empty$ - { organization empty$ - - { cite$ #1 #3 substring$ } - - { "The " #4 organization chop.word #3 text.prefix$ } - if$ - } - { key #3 text.prefix$ } - if$ - } - { author format.lab.names } - if$ -} - -FUNCTION {editor.key.organization.label} -{ editor empty$ - { key empty$ - { organization empty$ - - { cite$ #1 #3 substring$ } - - { "The " #4 organization chop.word #3 text.prefix$ } - if$ - } - { key #3 text.prefix$ } - if$ - } - { editor format.lab.names } - if$ -} - -FUNCTION {calc.label} -{ type$ "book" = - type$ "inbook" = - or - 'author.editor.key.label - { type$ "proceedings" = - 'editor.key.organization.label - { type$ "manual" = - 'author.key.organization.label - 'author.key.label - if$ - } - if$ - } - if$ - duplicate$ - - "\protect\citename{" swap$ * "}" * - year field.or.null purify$ * - 'label := - year field.or.null purify$ * - - sortify 'sort.label := -} - -FUNCTION {sort.format.names} -{ 's := - #1 'nameptr := - "" - s num.names$ 'numnames := - numnames 'namesleft := - { namesleft #0 > } - { nameptr #1 > - { " " * } - 'skip$ - if$ - - s nameptr "{vv{ } }{ll{ }}{ ff{ }}{ jj{ }}" format.name$ 't := - - nameptr numnames = t "others" = and - { "et al" * } - { t sortify * } - if$ - nameptr #1 + 'nameptr := - namesleft #1 - 'namesleft := - } - while$ -} - -FUNCTION {sort.format.title} -{ 't := - "A " #2 - "An " #3 - "The " #4 t chop.word - chop.word - chop.word - sortify - #1 global.max$ substring$ -} - -FUNCTION {author.sort} -{ author empty$ - { key empty$ - { "to sort, need author or key in " cite$ * warning$ - "" - } - { key sortify } - if$ - } - { author sort.format.names } - if$ -} - -FUNCTION {author.editor.sort} -{ author empty$ - { editor empty$ - { key empty$ - { "to sort, need author, editor, or key in " cite$ * warning$ - "" - } - { key sortify } - if$ - } - { editor sort.format.names } - if$ - } - { author sort.format.names } - if$ -} - -FUNCTION {author.organization.sort} -{ author empty$ - { organization empty$ - { key empty$ - { "to sort, need author, organization, or key in " cite$ * warning$ - "" - } - { key sortify } - if$ - } - { "The " #4 organization chop.word sortify } - if$ - } - { author sort.format.names } - if$ -} - -FUNCTION {editor.organization.sort} -{ editor empty$ - { organization empty$ - { key empty$ - { "to sort, need editor, organization, or key in " cite$ * warning$ - "" - } - { key sortify } - if$ - } - { "The " #4 organization chop.word sortify } - if$ - } - { editor sort.format.names } - if$ -} - -FUNCTION {presort} - -{ calc.label - sort.label - " " - * - type$ "book" = - - type$ "inbook" = - or - 'author.editor.sort - { type$ "proceedings" = - 'editor.organization.sort - { type$ "manual" = - 'author.organization.sort - 'author.sort - if$ - } - if$ - } - if$ - - * - - " " - * - year field.or.null sortify - * - " " - * - title field.or.null - sort.format.title - * - #1 entry.max$ substring$ - 'sort.key$ := -} - -ITERATE {presort} - -SORT - -STRINGS { longest.label last.sort.label next.extra } - -INTEGERS { longest.label.width last.extra.num } - -FUNCTION {initialize.longest.label} -{ "" 'longest.label := - #0 int.to.chr$ 'last.sort.label := - "" 'next.extra := - #0 'longest.label.width := - #0 'last.extra.num := -} - -FUNCTION {forward.pass} -{ last.sort.label sort.label = - { last.extra.num #1 + 'last.extra.num := - last.extra.num int.to.chr$ 'extra.label := - } - { "a" chr.to.int$ 'last.extra.num := - "" 'extra.label := - sort.label 'last.sort.label := - } - if$ -} - -FUNCTION {reverse.pass} -{ next.extra "b" = - { "a" 'extra.label := } - 'skip$ - if$ - label extra.label * 'label := - label width$ longest.label.width > - { label 'longest.label := - label width$ 'longest.label.width := - } - 'skip$ - if$ - extra.label 'next.extra := -} - -EXECUTE {initialize.longest.label} - -ITERATE {forward.pass} - -REVERSE {reverse.pass} - -FUNCTION {begin.bib} - -{ et.al.char.used - { "\newcommand{\etalchar}[1]{$^{#1}$}" write$ newline$ } - 'skip$ - if$ - preamble$ empty$ - - 'skip$ - { preamble$ write$ newline$ } - if$ - - "\begin{thebibliography}{" "}" * write$ newline$ - -} - -EXECUTE {begin.bib} - -EXECUTE {init.state.consts} - -ITERATE {call.type$} - -FUNCTION {end.bib} -{ newline$ - "\end{thebibliography}" write$ newline$ -} - -EXECUTE {end.bib} - diff --git a/report/pyp_clustering/acl09-short/common/naaclhlt2010.sty b/report/pyp_clustering/acl09-short/common/naaclhlt2010.sty deleted file mode 100644 index 0cf940ff..00000000 --- a/report/pyp_clustering/acl09-short/common/naaclhlt2010.sty +++ /dev/null @@ -1,343 +0,0 @@ -% File acl2010.sty -% October 11, 2004 -% Contact: oflazer@sabanciuniv.edu - -% This is the LaTeX style file for NAACL HLT 2010. It is nearly identical to the -% style files for ACL 2005, ACL 2002, ACL 2001, ACL 2000, EACL 95 and EACL -% 99. -% -% This is the LaTeX style file for ACL 2000. It is nearly identical to the -% style files for EACL 95 and EACL 99. Minor changes include editing the -% instructions to reflect use of \documentclass rather than \documentstyle -% and removing the white space before the title on the first page -% -- John Chen, June 29, 2000 - -% To convert from submissions prepared using the style file aclsub.sty -% prepared for the ACL 2000 conference, proceed as follows: -% 1) Remove submission-specific information: \whichsession, \id, -% \wordcount, \otherconferences, \area, \keywords -% 2) \summary should be removed. The summary material should come -% after \maketitle and should be in the ``abstract'' environment -% 3) Check all citations. This style should handle citations correctly -% and also allows multiple citations separated by semicolons. -% 4) Check figures and examples. Because the final format is double- -% column, some adjustments may have to be made to fit text in the column -% or to choose full-width (\figure*} figures. -% 5) Change the style reference from aclsub to acl2000, and be sure -% this style file is in your TeX search path - - -% This is the LaTeX style file for EACL-95. It is identical to the -% style file for ANLP '94 except that the margins are adjusted for A4 -% paper. -- abney 13 Dec 94 - -% The ANLP '94 style file is a slightly modified -% version of the style used for AAAI and IJCAI, using some changes -% prepared by Fernando Pereira and others and some minor changes -% by Paul Jacobs. - -% Papers prepared using the aclsub.sty file and acl.bst bibtex style -% should be easily converted to final format using this style. -% (1) Submission information (\wordcount, \subject, and \makeidpage) -% should be removed. -% (2) \summary should be removed. The summary material should come -% after \maketitle and should be in the ``abstract'' environment -% (between \begin{abstract} and \end{abstract}). -% (3) Check all citations. This style should handle citations correctly -% and also allows multiple citations separated by semicolons. -% (4) Check figures and examples. Because the final format is double- -% column, some adjustments may have to be made to fit text in the column -% or to choose full-width (\figure*} figures. - -% Place this in a file called aclap.sty in the TeX search path. -% (Placing it in the same directory as the paper should also work.) - -% Prepared by Peter F. Patel-Schneider, liberally using the ideas of -% other style hackers, including Barbara Beeton. -% This style is NOT guaranteed to work. It is provided in the hope -% that it will make the preparation of papers easier. -% -% There are undoubtably bugs in this style. If you make bug fixes, -% improvements, etc. please let me know. My e-mail address is: -% pfps@research.att.com - -% Papers are to be prepared using the ``acl'' bibliography style, -% as follows: -% \documentclass[11pt]{article} -% \usepackage{acl2000} -% \title{Title} -% \author{Author 1 \and Author 2 \\ Address line \\ Address line \And -% Author 3 \\ Address line \\ Address line} -% \begin{document} -% ... -% \bibliography{bibliography-file} -% \bibliographystyle{acl} -% \end{document} - -% Author information can be set in various styles: -% For several authors from the same institution: -% \author{Author 1 \and ... \and Author n \\ -% Address line \\ ... \\ Address line} -% if the names do not fit well on one line use -% Author 1 \\ {\bf Author 2} \\ ... \\ {\bf Author n} \\ -% For authors from different institutions: -% \author{Author 1 \\ Address line \\ ... \\ Address line -% \And ... \And -% Author n \\ Address line \\ ... \\ Address line} -% To start a seperate ``row'' of authors use \AND, as in -% \author{Author 1 \\ Address line \\ ... \\ Address line -% \AND -% Author 2 \\ Address line \\ ... \\ Address line \And -% Author 3 \\ Address line \\ ... \\ Address line} - -% If the title and author information does not fit in the area allocated, -% place \setlength\titlebox{} right after -% \usepackage{acl2000} -% where can be something larger than 2.25in - -% \typeout{Conference Style for ACL 2000 -- released June 20, 2000} -\typeout{Conference Style for NAACL-HLT 2010 -- released November 16, 2009} - -% NOTE: Some laser printers have a serious problem printing TeX output. -% These printing devices, commonly known as ``write-white'' laser -% printers, tend to make characters too light. To get around this -% problem, a darker set of fonts must be created for these devices. -% - -% Physical page layout - slightly modified from IJCAI by pj -\setlength\topmargin{0.0in} \setlength\oddsidemargin{-0.0in} -\setlength\textheight{9.0in} \setlength\textwidth{6.5in} -\setlength\columnsep{0.2in} -\newlength\titlebox -\setlength\titlebox{2.25in} -\setlength\headheight{0pt} \setlength\headsep{0pt} -%\setlength\footheight{0pt} -\setlength\footskip{0pt} -\thispagestyle{empty} \pagestyle{empty} -\flushbottom \twocolumn \sloppy - -%% A4 version of page layout -%\setlength\topmargin{-0.45cm} % changed by Rz -1.4 -%\setlength\oddsidemargin{.8mm} % was -0cm, changed by Rz -%\setlength\textheight{23.5cm} -%\setlength\textwidth{15.8cm} -%\setlength\columnsep{0.6cm} -%\newlength\titlebox -%\setlength\titlebox{2.00in} -%\setlength\headheight{5pt} -%\setlength\headsep{0pt} -%%\setlength\footheight{0pt} -%\setlength\footskip{0pt} -%\thispagestyle{empty} -%\pagestyle{empty} - -\flushbottom \twocolumn \sloppy - -% We're never going to need a table of contents, so just flush it to -% save space --- suggested by drstrip@sandia-2 -\def\addcontentsline#1#2#3{} - -% Title stuff, taken from deproc. -\def\maketitle{\par - \begingroup - \def\thefootnote{\fnsymbol{footnote}} - \def\@makefnmark{\hbox to 0pt{$^{\@thefnmark}$\hss}} - \twocolumn[\@maketitle] \@thanks - \endgroup - \setcounter{footnote}{0} - \let\maketitle\relax \let\@maketitle\relax - \gdef\@thanks{}\gdef\@author{}\gdef\@title{}\let\thanks\relax} -\def\@maketitle{\vbox to \titlebox{\hsize\textwidth - \linewidth\hsize \vskip 0.125in minus 0.125in \centering - {\Large\bf \@title \par} \vskip 0.2in plus 1fil minus 0.1in - {\def\and{\unskip\enspace{\rm and}\enspace}% - \def\And{\end{tabular}\hss \egroup \hskip 1in plus 2fil - \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf}% - \def\AND{\end{tabular}\hss\egroup \hfil\hfil\egroup - \vskip 0.25in plus 1fil minus 0.125in - \hbox to \linewidth\bgroup\large \hfil\hfil - \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf} - \hbox to \linewidth\bgroup\large \hfil\hfil - \hbox to 0pt\bgroup\hss \begin{tabular}[t]{c}\bf\@author - \end{tabular}\hss\egroup - \hfil\hfil\egroup} - \vskip 0.3in plus 2fil minus 0.1in -}} -\renewenvironment{abstract}{\centerline{\large\bf - Abstract}\vspace{0.5ex}\begin{quote} \small}{\par\end{quote}\vskip 1ex} - - -% bibliography - -\def\thebibliography#1{\section*{References} - \global\def\@listi{\leftmargin\leftmargini - \labelwidth\leftmargini \advance\labelwidth-\labelsep - \topsep 1pt plus 2pt minus 1pt - \parsep 0.25ex plus 1pt \itemsep 0.25ex plus 1pt} - \list {[\arabic{enumi}]}{\settowidth\labelwidth{[#1]}\leftmargin\labelwidth - \advance\leftmargin\labelsep\usecounter{enumi}} - \def\newblock{\hskip .11em plus .33em minus -.07em} - \sloppy - \sfcode`\.=1000\relax} - -\def\@up#1{\raise.2ex\hbox{#1}} - -% most of cite format is from aclsub.sty by SMS - -% don't box citations, separate with ; and a space -% also, make the penalty between citations negative: a good place to break -% changed comma back to semicolon pj 2/1/90 -% \def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi -% \def\@citea{}\@cite{\@for\@citeb:=#2\do -% {\@citea\def\@citea{;\penalty\@citeseppen\ }\@ifundefined -% {b@\@citeb}{{\bf ?}\@warning -% {Citation `\@citeb' on page \thepage \space undefined}}% -% {\csname b@\@citeb\endcsname}}}{#1}} - -% don't box citations, separate with ; and a space -% Replaced for multiple citations (pj) -% don't box citations and also add space, semicolon between multiple citations -\def\@citex[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi - \def\@citea{}\@cite{\@for\@citeb:=#2\do - {\@citea\def\@citea{; }\@ifundefined - {b@\@citeb}{{\bf ?}\@warning - {Citation `\@citeb' on page \thepage \space undefined}}% - {\csname b@\@citeb\endcsname}}}{#1}} - -% Allow short (name-less) citations, when used in -% conjunction with a bibliography style that creates labels like -% \citename{, } -% -\let\@internalcite\cite -\def\cite{\def\citename##1{##1, }\@internalcite} -\def\shortcite{\def\citename##1{}\@internalcite} -\def\newcite{\def\citename##1{{\frenchspacing##1} (}\@internalciteb} - -% Macros for \newcite, which leaves name in running text, and is -% otherwise like \shortcite. -\def\@citexb[#1]#2{\if@filesw\immediate\write\@auxout{\string\citation{#2}}\fi - \def\@citea{}\@newcite{\@for\@citeb:=#2\do - {\@citea\def\@citea{;\penalty\@m\ }\@ifundefined - {b@\@citeb}{{\bf ?}\@warning - {Citation `\@citeb' on page \thepage \space undefined}}% -{\csname b@\@citeb\endcsname}}}{#1}} -\def\@internalciteb{\@ifnextchar [{\@tempswatrue\@citexb}{\@tempswafalse\@citexb[]}} - -\def\@newcite#1#2{{#1\if@tempswa, #2\fi)}} - -\def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} - -%%% More changes made by SMS (originals in latex.tex) -% Use parentheses instead of square brackets in the text. -\def\@cite#1#2{({#1\if@tempswa , #2\fi})} - -% Don't put a label in the bibliography at all. Just use the unlabeled format -% instead. -\def\thebibliography#1{\small\vskip\parskip% -\vskip\baselineskip% -\def\baselinestretch{1}% -\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% -\vskip-\parskip% -\vskip-\baselineskip% -\section*{References\@mkboth - {References}{References}}\list - {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} - \setlength{\itemsep}{-0.5ex} - \setlength{\itemindent}{-\parindent}} - \def\newblock{\hskip .11em plus .33em minus -.07em} - \sloppy\clubpenalty4000\widowpenalty4000 - \sfcode`\.=1000\relax} -\let\endthebibliography=\endlist - -% Allow for a bibliography of sources of attested examples -\def\thesourcebibliography#1{\vskip\parskip% -\vskip\baselineskip% -\def\baselinestretch{1}% -\ifx\@currsize\normalsize\@normalsize\else\@currsize\fi% -\vskip-\parskip% -\vskip-\baselineskip% -\section*{Sources of Attested Examples\@mkboth - {Sources of Attested Examples}{Sources of Attested Examples}}\list - {}{\setlength{\labelwidth}{0pt}\setlength{\leftmargin}{\parindent} - \setlength{\itemindent}{-\parindent}} - \def\newblock{\hskip .11em plus .33em minus -.07em} - \sloppy\clubpenalty4000\widowpenalty4000 - \sfcode`\.=1000\relax} -\let\endthesourcebibliography=\endlist - -\def\@lbibitem[#1]#2{\item[]\if@filesw - { \def\protect##1{\string ##1\space}\immediate - \write\@auxout{\string\bibcite{#2}{#1}}\fi\ignorespaces}} - -\def\@bibitem#1{\item\if@filesw \immediate\write\@auxout - {\string\bibcite{#1}{\the\c@enumi}}\fi\ignorespaces} - -% sections with less space -\def\section{\@startsection {section}{1}{\z@}{-2.0ex plus - -0.5ex minus -.2ex}{1.5ex plus 0.3ex minus .2ex}{\large\bf\raggedright}} -\def\subsection{\@startsection{subsection}{2}{\z@}{-1.8ex plus - -0.5ex minus -.2ex}{0.8ex plus .2ex}{\normalsize\bf\raggedright}} -\def\subsubsection{\@startsection{subsubsection}{3}{\z@}{1.5ex plus - 0.5ex minus .2ex}{0.5ex plus .2ex}{\normalsize\bf\raggedright}} -\def\paragraph{\@startsection{paragraph}{4}{\z@}{1.5ex plus - 0.5ex minus .2ex}{-1em}{\normalsize\bf}} -\def\subparagraph{\@startsection{subparagraph}{5}{\parindent}{1.5ex plus - 0.5ex minus .2ex}{-1em}{\normalsize\bf}} - -% Footnotes -\footnotesep 6.65pt % -\skip\footins 9pt plus 4pt minus 2pt -\def\footnoterule{\kern-3pt \hrule width 5pc \kern 2.6pt } -\setcounter{footnote}{0} - -% Lists and paragraphs -\parindent 1em -\topsep 4pt plus 1pt minus 2pt -\partopsep 1pt plus 0.5pt minus 0.5pt -\itemsep 2pt plus 1pt minus 0.5pt -\parsep 2pt plus 1pt minus 0.5pt - -\leftmargin 2em \leftmargini\leftmargin \leftmarginii 2em -\leftmarginiii 1.5em \leftmarginiv 1.0em \leftmarginv .5em \leftmarginvi .5em -\labelwidth\leftmargini\advance\labelwidth-\labelsep \labelsep 5pt - -\def\@listi{\leftmargin\leftmargini} -\def\@listii{\leftmargin\leftmarginii - \labelwidth\leftmarginii\advance\labelwidth-\labelsep - \topsep 2pt plus 1pt minus 0.5pt - \parsep 1pt plus 0.5pt minus 0.5pt - \itemsep \parsep} -\def\@listiii{\leftmargin\leftmarginiii - \labelwidth\leftmarginiii\advance\labelwidth-\labelsep - \topsep 1pt plus 0.5pt minus 0.5pt - \parsep \z@ \partopsep 0.5pt plus 0pt minus 0.5pt - \itemsep \topsep} -\def\@listiv{\leftmargin\leftmarginiv - \labelwidth\leftmarginiv\advance\labelwidth-\labelsep} -\def\@listv{\leftmargin\leftmarginv - \labelwidth\leftmarginv\advance\labelwidth-\labelsep} -\def\@listvi{\leftmargin\leftmarginvi - \labelwidth\leftmarginvi\advance\labelwidth-\labelsep} - -\abovedisplayskip 7pt plus2pt minus5pt% -\belowdisplayskip \abovedisplayskip -\abovedisplayshortskip 0pt plus3pt% -\belowdisplayshortskip 4pt plus3pt minus3pt% - -% Less leading in most fonts (due to the narrow columns) -% The choices were between 1-pt and 1.5-pt leading -%\def\@normalsize{\@setsize\normalsize{11pt}\xpt\@xpt} -%\def\small{\@setsize\small{10pt}\ixpt\@ixpt} -%\def\footnotesize{\@setsize\footnotesize{10pt}\ixpt\@ixpt} -%\def\scriptsize{\@setsize\scriptsize{8pt}\viipt\@viipt} -%\def\tiny{\@setsize\tiny{7pt}\vipt\@vipt} -%\def\large{\@setsize\large{14pt}\xiipt\@xiipt} -%\def\Large{\@setsize\Large{16pt}\xivpt\@xivpt} -%\def\LARGE{\@setsize\LARGE{20pt}\xviipt\@xviipt} -%\def\huge{\@setsize\huge{23pt}\xxpt\@xxpt} -%\def\Huge{\@setsize\Huge{28pt}\xxvpt\@xxvpt} - -\let\@@makecaption\@makecaption -\renewcommand{\@makecaption}[1]{\@@makecaption{\small #1}} - -\newcommand{\Thanks}[1]{\thanks{\ #1}} \ No newline at end of file diff --git a/report/pyp_clustering/acl09-short/common/prettyref.sty b/report/pyp_clustering/acl09-short/common/prettyref.sty deleted file mode 100644 index 67940f3b..00000000 --- a/report/pyp_clustering/acl09-short/common/prettyref.sty +++ /dev/null @@ -1,37 +0,0 @@ -%% -%% This is file `prettyref.sty', -%% generated with the docstrip utility. -%% -%% The original source files were: -%% -%% prettyref.dtx (with options: `style') -%% -%% Copyright (c) 1995 Kevin Ruland -%% -%% -%% prettyref v3.0 -%% -%% Copyright 1995,1998. by Kevin Ruland kevin@rodin.wustl.edu -%% -\ProvidesPackage{prettyref}[1998/07/09 v3.0] -\def\newrefformat#1#2{% - \@namedef{pr@#1}##1{#2}} -\newrefformat{eq}{\textup{(\ref{#1})}} -\newrefformat{lem}{Lemma \ref{#1}} -\newrefformat{thm}{Theorem \ref{#1}} -\newrefformat{cha}{Chapter \ref{#1}} -\newrefformat{sec}{Section \ref{#1}} -\newrefformat{tab}{Table \ref{#1} on page \pageref{#1}} -\newrefformat{fig}{Figure \ref{#1} on page \pageref{#1}} -\def\prettyref#1{\@prettyref#1:} -\def\@prettyref#1:#2:{% - \expandafter\ifx\csname pr@#1\endcsname\relax% - \PackageWarning{prettyref}{Reference format #1\space undefined}% - \ref{#1:#2}% - \else% - \csname pr@#1\endcsname{#1:#2}% - \fi% -} -\endinput -%% -%% End of file `prettyref.sty'. diff --git a/report/pyp_clustering/acl09-short/common/scrunchacl.bst b/report/pyp_clustering/acl09-short/common/scrunchacl.bst deleted file mode 100644 index 26e1fca6..00000000 --- a/report/pyp_clustering/acl09-short/common/scrunchacl.bst +++ /dev/null @@ -1,1317 +0,0 @@ - -% BibTeX `scrunchacl' style file made by modifying `acl' style file. -% Lillian Lee, February 2003. Abbreviate first names, no explicit -% marker for page numbers, -% "editors" -> "eds", but still consistent with `fullname.sty'. No -% "and" between multiple authors. -% Also, might still have trouble with double-years, sometimes - -% BibTeX `acl' style file for BibTeX version 0.99c, LaTeX version 2.09 -% This version was made by modifying `aaai-named' format based on the master -% file by Oren Patashnik (PATASHNIK@SCORE.STANFORD.EDU) - -% Copyright (C) 1985, all rights reserved. -% Modifications Copyright 1988, Peter F. Patel-Schneider -% Further modifictions by Stuart Shieber, 1991, and Fernando Pereira, 1992. -% Copying of this file is authorized only if either -% (1) you make absolutely no changes to your copy, including name, or -% (2) if you do make changes, you name it something other than -% btxbst.doc, plain.bst, unsrt.bst, alpha.bst, and abbrv.bst. -% This restriction helps ensure that all standard styles are identical. - -% There are undoubtably bugs in this style. If you make bug fixes, -% improvements, etc. please let me know. My e-mail address is: -% pfps@spar.slb.com - -% Citation format: [author-last-name, year] -% [author-last-name and author-last-name, year] -% [author-last-name {\em et al.}, year] -% -% Reference list ordering: alphabetical by author or whatever passes -% for author in the absence of one. -% -% This BibTeX style has support for short (year only) citations. This -% is done by having the citations actually look like -% \citename{name-info, }year -% The LaTeX style has to have the following -% \let\@internalcite\cite -% \def\cite{\def\citename##1{##1}\@internalcite} -% \def\shortcite{\def\citename##1{}\@internalcite} -% \def\@biblabel#1{\def\citename##1{##1}[#1]\hfill} -% which makes \shortcite the macro for short citations. - -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% -% Changes made by SMS for thesis style -% no emphasis on "et al." -% "Ph.D." includes periods (not "PhD") -% moved year to immediately after author's name -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% -ENTRY - { address - author - booktitle - chapter - edition - editor - howpublished - institution - journal - key - month - note - number - organization - pages - publisher - school - series - title - type - volume - year - } - {} - { label extra.label sort.label } - -INTEGERS { output.state before.all mid.sentence after.sentence after.block } - -FUNCTION {init.state.consts} -{ #0 'before.all := - #1 'mid.sentence := - #2 'after.sentence := - #3 'after.block := -} - -STRINGS { s t } - -FUNCTION {output.nonnull} -{ 's := - output.state mid.sentence = - { ", " * write$ } - { output.state after.block = - { add.period$ write$ - newline$ - "\newblock " write$ - } - { output.state before.all = - 'write$ - { add.period$ " " * write$ } - if$ - } - if$ - mid.sentence 'output.state := - } - if$ - s -} - -FUNCTION {output} -{ duplicate$ empty$ - 'pop$ - 'output.nonnull - if$ -} - -FUNCTION {output.check} -{ 't := - duplicate$ empty$ - { pop$ "empty " t * " in " * cite$ * warning$ } - 'output.nonnull - if$ -} - - -FUNCTION {output.bibitem} -{ - "\bibitem[" write$ - label write$ - "]{" write$ - - cite$ write$ - "}" write$ - "" - before.all 'output.state := -} - -FUNCTION {fin.entry} -{ add.period$ - write$ - "\bibsnip" write$ - newline$ -} - -FUNCTION {new.block} -{ output.state before.all = - 'skip$ - { after.block 'output.state := } - if$ -} - -FUNCTION {new.sentence} -{ output.state after.block = - 'skip$ - { output.state before.all = - 'skip$ - { after.sentence 'output.state := } - if$ - } - if$ -} - -FUNCTION {not} -{ { #0 } - { #1 } - if$ -} - -FUNCTION {and} -{ 'skip$ - { pop$ #0 } - if$ -} - -FUNCTION {or} -{ { pop$ #1 } - 'skip$ - if$ -} - -FUNCTION {new.block.checka} -{ empty$ - 'skip$ - 'new.block - if$ -} - -FUNCTION {new.block.checkb} -{ empty$ - swap$ empty$ - and - 'skip$ - 'new.block - if$ -} - -FUNCTION {new.sentence.checka} -{ empty$ - 'skip$ - 'new.sentence - if$ -} - -FUNCTION {new.sentence.checkb} -{ empty$ - swap$ empty$ - and - 'skip$ - 'new.sentence - if$ -} - -FUNCTION {field.or.null} -{ duplicate$ empty$ - { pop$ "" } - 'skip$ - if$ -} - -FUNCTION {emphasize} -{ duplicate$ empty$ - { pop$ "" } - { "{\em " swap$ * "}" * } - if$ -} - -INTEGERS { nameptr namesleft numnames } - - - -FUNCTION {format.names} -{ 's := - #1 'nameptr := - s num.names$ 'numnames := - numnames 'namesleft := - { namesleft #0 > } - { s nameptr "{f.~}{vv~}{ll}{, jj}" format.name$ 't := - nameptr #1 > - { namesleft #1 > - { ", " * t * } - { numnames #2 > - { "" * } - 'skip$ - if$ - t "others" = - { " et~al." * } - { ", " * t * } - if$ - } - if$ - } - 't - if$ - nameptr #1 + 'nameptr := - namesleft #1 - 'namesleft := - } - while$ -} - -FUNCTION {format.authors} -{ author empty$ - { "" } - { author format.names } - if$ -} - -FUNCTION {format.editors} -{ editor empty$ - { "" } - { editor format.names - editor num.names$ #1 > - { ", eds." * } - { ", ed." * } - if$ - } - if$ -} - -FUNCTION {format.title} -{ title empty$ - { "" } - { title "t" change.case$ } - if$ -} - -FUNCTION {n.dashify} -{ 't := - "" - { t empty$ not } - { t #1 #1 substring$ "-" = - { t #1 #2 substring$ "--" = not - { "--" * - t #2 global.max$ substring$ 't := - } - { { t #1 #1 substring$ "-" = } - { "-" * - t #2 global.max$ substring$ 't := - } - while$ - } - if$ - } - { t #1 #1 substring$ * - t #2 global.max$ substring$ 't := - } - if$ - } - while$ -} - -FUNCTION {format.date} -{ year empty$ - { month empty$ - { "" } - { "there's a month but no year in " cite$ * warning$ - month - } - if$ - } - { month empty$ - 'year - { month " " * year * } - if$ - } - if$ -} - -FUNCTION {format.btitle} -{ title emphasize -} - -FUNCTION {tie.or.space.connect} -{ duplicate$ text.length$ #3 < - { "~" } - { " " } - if$ - swap$ * * -} - -FUNCTION {either.or.check} -{ empty$ - 'pop$ - { "can't use both " swap$ * " fields in " * cite$ * warning$ } - if$ -} - -FUNCTION {format.bvolume} -{ volume empty$ - { "" } - { "volume" volume tie.or.space.connect - series empty$ - 'skip$ - { " of " * series emphasize * } - if$ - "volume and number" number either.or.check - } - if$ -} - -FUNCTION {format.number.series} -{ volume empty$ - { number empty$ - { series field.or.null } - { output.state mid.sentence = - { "number" } - { "Number" } - if$ - number tie.or.space.connect - series empty$ - { "there's a number but no series in " cite$ * warning$ } - { " in " * series * } - if$ - } - if$ - } - { "" } - if$ -} - -FUNCTION {format.edition} -{ edition empty$ - { "" } - { output.state mid.sentence = - { edition "l" change.case$ " edition" * } - { edition "t" change.case$ " edition" * } - if$ - } - if$ -} - -INTEGERS { multiresult } - -FUNCTION {multi.page.check} -{ 't := - #0 'multiresult := - { multiresult not - t empty$ not - and - } - { t #1 #1 substring$ - duplicate$ "-" = - swap$ duplicate$ "," = - swap$ "+" = - or or - { #1 'multiresult := } - { t #2 global.max$ substring$ 't := } - if$ - } - while$ - multiresult -} - -FUNCTION {format.pages} -{ pages empty$ - { "" } - { pages multi.page.check - { "" pages n.dashify tie.or.space.connect } - { "pg." pages tie.or.space.connect } - if$ - } - if$ -} - -FUNCTION {format.year.label} -{ year extra.label * -} - -FUNCTION {format.vol.num.pages} -{ volume field.or.null - number empty$ - 'skip$ - { "(" number * ")" * * - volume empty$ - { "there's a number but no volume in " cite$ * warning$ } - 'skip$ - if$ - } - if$ - pages empty$ - 'skip$ - { duplicate$ empty$ - { pop$ format.pages } - { ":" * pages n.dashify * } - if$ - } - if$ -} - -FUNCTION {format.chapter.pages} -{ chapter empty$ - 'format.pages - { type empty$ - { "chapter" } - { type "l" change.case$ } - if$ - chapter tie.or.space.connect - pages empty$ - 'skip$ - { ", " * format.pages * } - if$ - } - if$ -} - -FUNCTION {format.in.ed.booktitle} -{ booktitle empty$ - { "" } - { editor empty$ - { "In " booktitle emphasize * } - { "In " format.editors * ", " * booktitle emphasize * } - if$ - } - if$ -} - -FUNCTION {empty.misc.check} -{ author empty$ title empty$ howpublished empty$ - month empty$ year empty$ note empty$ - and and and and and - - key empty$ not and - - { "all relevant fields are empty in " cite$ * warning$ } - 'skip$ - if$ -} - -FUNCTION {format.thesis.type} -{ type empty$ - 'skip$ - { pop$ - type "t" change.case$ - } - if$ -} - -FUNCTION {format.tr.number} -{ type empty$ - { "Technical Report" } - 'type - if$ - number empty$ - { "t" change.case$ } - { number tie.or.space.connect } - if$ -} - -FUNCTION {format.article.crossref} -{ key empty$ - { journal empty$ - { "need key or journal for " cite$ * " to crossref " * crossref * - warning$ - "" - } - { "In {\em " journal * "\/}" * } - if$ - } - { "In " key * } - if$ - " \cite{" * crossref * "}" * -} - -FUNCTION {format.crossref.editor} -{ editor #1 "{vv~}{ll}" format.name$ - editor num.names$ duplicate$ - #2 > - { pop$ " et~al." * } - { #2 < - 'skip$ - { editor #2 "{ff }{vv }{ll}{ jj}" format.name$ "others" = - { " et~al." * } - { " and " * editor #2 "{vv~}{ll}" format.name$ * } - if$ - } - if$ - } - if$ -} - -FUNCTION {format.book.crossref} -{ volume empty$ - { "empty volume in " cite$ * "'s crossref of " * crossref * warning$ - "In " - } - { "Volume" volume tie.or.space.connect - " of " * - } - if$ - editor empty$ - editor field.or.null author field.or.null = - or - { key empty$ - { series empty$ - { "need editor, key, or series for " cite$ * " to crossref " * - crossref * warning$ - "" * - } - { "{\em " * series * "\/}" * } - if$ - } - { key * } - if$ - } - { format.crossref.editor * } - if$ - " \cite{" * crossref * "}" * -} - -FUNCTION {format.incoll.inproc.crossref} -{ editor empty$ - editor field.or.null author field.or.null = - or - { key empty$ - { booktitle empty$ - { "need editor, key, or booktitle for " cite$ * " to crossref " * - crossref * warning$ - "" - } - { "In {\em " booktitle * "\/}" * } - if$ - } - { "In " key * } - if$ - } - { "In " format.crossref.editor * } - if$ - " \cite{" * crossref * "}" * -} - -FUNCTION {article} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - crossref missing$ - { journal emphasize "journal" output.check - format.vol.num.pages output - } - { format.article.crossref output.nonnull - format.pages output - } - if$ - new.block - note output - fin.entry -} - -FUNCTION {book} -{ output.bibitem - author empty$ - { format.editors "author and editor" output.check } - { format.authors output.nonnull - crossref missing$ - { "author and editor" editor either.or.check } - 'skip$ - if$ - } - if$ - new.block - format.year.label "year" output.check - new.block - format.btitle "title" output.check - crossref missing$ - { format.bvolume output - new.block - format.number.series output - new.sentence - publisher "publisher" output.check - address output - } - { new.block - format.book.crossref output.nonnull - } - if$ - format.edition output - note output - fin.entry -} - -FUNCTION {booklet} -{ output.bibitem - format.authors output - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - howpublished address new.block.checkb - howpublished output - address output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {inbook} -{ output.bibitem - author empty$ - { format.editors "author and editor" output.check } - { format.authors output.nonnull - crossref missing$ - { "author and editor" editor either.or.check } - 'skip$ - if$ - } - if$ - format.year.label "year" output.check - new.block - new.block - format.btitle "title" output.check - crossref missing$ - { format.bvolume output - format.chapter.pages "chapter and pages" output.check - new.block - format.number.series output - new.sentence - publisher "publisher" output.check - address output - } - { format.chapter.pages "chapter and pages" output.check - new.block - format.book.crossref output.nonnull - } - if$ - format.edition output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {incollection} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - crossref missing$ - { format.in.ed.booktitle "booktitle" output.check - format.bvolume output - format.number.series output - format.chapter.pages output - new.sentence - publisher "publisher" output.check - address output - format.edition output - } - { format.incoll.inproc.crossref output.nonnull - format.chapter.pages output - } - if$ - new.block - note output - fin.entry -} - -FUNCTION {inproceedings} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - crossref missing$ - { format.in.ed.booktitle "booktitle" output.check - format.bvolume output - format.number.series output - format.pages output - address empty$ - { organization publisher new.sentence.checkb - organization output - publisher output - } - { address output.nonnull - new.sentence - organization output - publisher output - } - if$ - } - { format.incoll.inproc.crossref output.nonnull - format.pages output - } - if$ - new.block - note output - fin.entry -} - -FUNCTION {conference} { inproceedings } - -FUNCTION {manual} -{ output.bibitem - author empty$ - { organization empty$ - 'skip$ - { organization output.nonnull - address output - } - if$ - } - { format.authors output.nonnull } - if$ - format.year.label "year" output.check - new.block - new.block - format.btitle "title" output.check - author empty$ - { organization empty$ - { address new.block.checka - address output - } - 'skip$ - if$ - } - { organization address new.block.checkb - organization output - address output - } - if$ - format.edition output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {mastersthesis} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - "Master's thesis" format.thesis.type output.nonnull - school "school" output.check - address output - note output - fin.entry -} - -FUNCTION {misc} -{ output.bibitem - format.authors output - new.block - format.year.label output - new.block - title howpublished new.block.checkb - format.title output - howpublished new.block.checka - howpublished output - format.date output - new.block - note output - fin.entry - empty.misc.check -} - -FUNCTION {phdthesis} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.btitle "title" output.check - new.block - "{Ph.D.} thesis" format.thesis.type output.nonnull - school "school" output.check - address output - note output - fin.entry -} - -FUNCTION {proceedings} -{ output.bibitem - editor empty$ - { organization output } - { format.editors output.nonnull } - if$ - new.block - format.year.label "year" output.check - new.block - format.btitle "title" output.check - format.bvolume output - format.number.series output - address empty$ - { editor empty$ - { publisher new.sentence.checka } - { organization publisher new.sentence.checkb - organization output - } - if$ - publisher output - format.date output - } - { address output.nonnull - format.date output - new.sentence - editor empty$ - 'skip$ - { organization output } - if$ - publisher output - } - if$ - new.block - note output - fin.entry -} - -FUNCTION {techreport} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - format.tr.number output.nonnull - institution "institution" output.check - address output - format.date output - new.block - note output - fin.entry -} - -FUNCTION {unpublished} -{ output.bibitem - format.authors "author" output.check - new.block - format.year.label "year" output.check - new.block - format.title "title" output.check - new.block - note "note" output.check - fin.entry -} - -FUNCTION {default.type} { misc } - -MACRO {jan} {"January"} - -MACRO {feb} {"February"} - -MACRO {mar} {"March"} - -MACRO {apr} {"April"} - -MACRO {may} {"May"} - -MACRO {jun} {"June"} - -MACRO {jul} {"July"} - -MACRO {aug} {"August"} - -MACRO {sep} {"September"} - -MACRO {oct} {"October"} - -MACRO {nov} {"November"} - -MACRO {dec} {"December"} - -MACRO {acmcs} {"ACM Computing Surveys"} - -MACRO {acta} {"Acta Informatica"} - -MACRO {cacm} {"Communications of the ACM"} - -MACRO {ibmjrd} {"IBM Journal of Research and Development"} - -MACRO {ibmsj} {"IBM Systems Journal"} - -MACRO {ieeese} {"IEEE Transactions on Software Engineering"} - -MACRO {ieeetc} {"IEEE Transactions on Computers"} - -MACRO {ieeetcad} - {"IEEE Transactions on Computer-Aided Design of Integrated Circuits"} - -MACRO {ipl} {"Information Processing Letters"} - -MACRO {jacm} {"Journal of the ACM"} - -MACRO {jcss} {"Journal of Computer and System Sciences"} - -MACRO {scp} {"Science of Computer Programming"} - -MACRO {sicomp} {"SIAM Journal on Computing"} - -MACRO {tocs} {"ACM Transactions on Computer Systems"} - -MACRO {tods} {"ACM Transactions on Database Systems"} - -MACRO {tog} {"ACM Transactions on Graphics"} - -MACRO {toms} {"ACM Transactions on Mathematical Software"} - -MACRO {toois} {"ACM Transactions on Office Information Systems"} - -MACRO {toplas} {"ACM Transactions on Programming Languages and Systems"} - -MACRO {tcs} {"Theoretical Computer Science"} - -READ - -FUNCTION {sortify} -{ purify$ - "l" change.case$ -} - -INTEGERS { len } - -FUNCTION {chop.word} -{ 's := - 'len := - s #1 len substring$ = - { s len #1 + global.max$ substring$ } - 's - if$ -} - -INTEGERS { et.al.char.used } - -FUNCTION {initialize.et.al.char.used} -{ #0 'et.al.char.used := -} - -EXECUTE {initialize.et.al.char.used} - -FUNCTION {format.lab.names} -{ 's := - s num.names$ 'numnames := - - numnames #1 = - { s #1 "{vv }{ll}" format.name$ } - { numnames #2 = - { s #1 "{vv }{ll }and " format.name$ s #2 "{vv }{ll}" format.name$ * - } - { s #1 "{vv }{ll }\bgroup et al.\egroup " format.name$ } - if$ - } - if$ - -} - -FUNCTION {author.key.label} -{ author empty$ - { key empty$ - - { cite$ #1 #3 substring$ } - - { key #3 text.prefix$ } - if$ - } - { author format.lab.names } - if$ -} - -FUNCTION {author.editor.key.label} -{ author empty$ - { editor empty$ - { key empty$ - - { cite$ #1 #3 substring$ } - - { key #3 text.prefix$ } - if$ - } - { editor format.lab.names } - if$ - } - { author format.lab.names } - if$ -} - -FUNCTION {author.key.organization.label} -{ author empty$ - { key empty$ - { organization empty$ - - { cite$ #1 #3 substring$ } - - { "The " #4 organization chop.word #3 text.prefix$ } - if$ - } - { key #3 text.prefix$ } - if$ - } - { author format.lab.names } - if$ -} - -FUNCTION {editor.key.organization.label} -{ editor empty$ - { key empty$ - { organization empty$ - - { cite$ #1 #3 substring$ } - - { "The " #4 organization chop.word #3 text.prefix$ } - if$ - } - { key #3 text.prefix$ } - if$ - } - { editor format.lab.names } - if$ -} - -FUNCTION {calc.label} -{ type$ "book" = - type$ "inbook" = - or - 'author.editor.key.label - { type$ "proceedings" = - 'editor.key.organization.label - { type$ "manual" = - 'author.key.organization.label - 'author.key.label - if$ - } - if$ - } - if$ - duplicate$ - - "\protect\citename{" swap$ * "}" * - year field.or.null purify$ * - 'label := - year field.or.null purify$ * - - sortify 'sort.label := -} - -FUNCTION {sort.format.names} -{ 's := - #1 'nameptr := - "" - s num.names$ 'numnames := - numnames 'namesleft := - { namesleft #0 > } - { nameptr #1 > - { " " * } - 'skip$ - if$ - - s nameptr "{vv{ } }{ll{ }}{ ff{ }}{ jj{ }}" format.name$ 't := - - nameptr numnames = t "others" = and - { "et al" * } - { t sortify * } - if$ - nameptr #1 + 'nameptr := - namesleft #1 - 'namesleft := - } - while$ -} - -FUNCTION {sort.format.title} -{ 't := - "A " #2 - "An " #3 - "The " #4 t chop.word - chop.word - chop.word - sortify - #1 global.max$ substring$ -} - -FUNCTION {author.sort} -{ author empty$ - { key empty$ - { "to sort, need author or key in " cite$ * warning$ - "" - } - { key sortify } - if$ - } - { author sort.format.names } - if$ -} - -FUNCTION {author.editor.sort} -{ author empty$ - { editor empty$ - { key empty$ - { "to sort, need author, editor, or key in " cite$ * warning$ - "" - } - { key sortify } - if$ - } - { editor sort.format.names } - if$ - } - { author sort.format.names } - if$ -} - -FUNCTION {author.organization.sort} -{ author empty$ - { organization empty$ - { key empty$ - { "to sort, need author, organization, or key in " cite$ * warning$ - "" - } - { key sortify } - if$ - } - { "The " #4 organization chop.word sortify } - if$ - } - { author sort.format.names } - if$ -} - -FUNCTION {editor.organization.sort} -{ editor empty$ - { organization empty$ - { key empty$ - { "to sort, need editor, organization, or key in " cite$ * warning$ - "" - } - { key sortify } - if$ - } - { "The " #4 organization chop.word sortify } - if$ - } - { editor sort.format.names } - if$ -} - -FUNCTION {presort} - -{ calc.label - sort.label - " " - * - type$ "book" = - - type$ "inbook" = - or - 'author.editor.sort - { type$ "proceedings" = - 'editor.organization.sort - { type$ "manual" = - 'author.organization.sort - 'author.sort - if$ - } - if$ - } - if$ - - * - - " " - * - year field.or.null sortify - * - " " - * - title field.or.null - sort.format.title - * - #1 entry.max$ substring$ - 'sort.key$ := -} - -ITERATE {presort} - -SORT - -STRINGS { longest.label last.sort.label next.extra } - -INTEGERS { longest.label.width last.extra.num } - -FUNCTION {initialize.longest.label} -{ "" 'longest.label := - #0 int.to.chr$ 'last.sort.label := - "" 'next.extra := - #0 'longest.label.width := - #0 'last.extra.num := -} - -FUNCTION {forward.pass} -{ last.sort.label sort.label = - { last.extra.num #1 + 'last.extra.num := - last.extra.num int.to.chr$ 'extra.label := - } - { "a" chr.to.int$ 'last.extra.num := - "" 'extra.label := - sort.label 'last.sort.label := - } - if$ -} - -FUNCTION {reverse.pass} -{ next.extra "b" = - { "a" 'extra.label := } - 'skip$ - if$ - label extra.label * 'label := - label width$ longest.label.width > - { label 'longest.label := - label width$ 'longest.label.width := - } - 'skip$ - if$ - extra.label 'next.extra := -} - -EXECUTE {initialize.longest.label} - -ITERATE {forward.pass} - -REVERSE {reverse.pass} - -FUNCTION {begin.bib} - -{ et.al.char.used - { "\newcommand{\etalchar}[1]{$^{#1}$}" write$ newline$ } - 'skip$ - if$ - preamble$ empty$ - - 'skip$ - { preamble$ write$ newline$ } - if$ - - "\begin{thebibliography}{" "}" * write$ newline$ - -} - -EXECUTE {begin.bib} - -EXECUTE {init.state.consts} - -ITERATE {call.type$} - -FUNCTION {end.bib} -{ newline$ - "\end{thebibliography}" write$ newline$ -} - -EXECUTE {end.bib} - - diff --git a/report/pyp_clustering/acl09-short/common/standard.bib b/report/pyp_clustering/acl09-short/common/standard.bib deleted file mode 100644 index fa4e9a8a..00000000 --- a/report/pyp_clustering/acl09-short/common/standard.bib +++ /dev/null @@ -1,2854 +0,0 @@ -%% This BibTeX bibliography file was created using BibDesk. -%% http://bibdesk.sourceforge.net/ - - -%% Created for Phil Blunsom at 2009-11-29 15:52:57 +0000 - - -%% Saved with string encoding Unicode (UTF-8) - - -@string{+aaai1980 = {Proc.\ of the 1st Conference on Artificial Intelligence (AAAI-80)}} - -@string{+aaai1991 = {Proc.\ of the 9th Annual Conference on Artificial Intelligence (AAAI-91)}} - -@string{+acl1983 = {Proc.\ of the 21st Annual Meeting of the ACL}} - -@string{+acl1984 = {Proc.\ of the 22nd Annual Meeting of the ACL}} - -@string{+acl1985 = {Proc.\ of the 23rd Annual Meeting of the ACL}} - -@string{+acl1986 = {Proc.\ of the 24th Annual Meeting of the ACL}} - -@string{+acl1987 = {Proc.\ of the 25th Annual Meeting of the ACL}} - -@string{+acl1988 = {Proc.\ of the 26th Annual Meeting of the ACL}} - -@string{+acl1989 = {Proc.\ of the 27th Annual Meeting of the ACL}} - -@string{+acl1990 = {Proc.\ of the 28th Annual Meeting of the ACL}} - -@string{+acl1991 = {Proc.\ of the 29th Annual Meeting of the ACL}} - -@string{+acl1992 = {Proc.\ of the 30th Annual Meeting of the ACL}} - -@string{+acl1992-ss = {Proc.\ of the 30th Annual Meeting of the ACL, Student Session}} - -@string{+acl1993 = {Proc.\ of the 31st Annual Meeting of the ACL}} - -@string{+acl1994 = {Proc.\ of the 32nd Annual Meeting of the ACL}} - -@string{+acl1995 = {Proc.\ of the 33rd Annual Meeting of the ACL}} - -@string{+acl1996 = {Proc.\ of the 34th Annual Meeting of the ACL}} - -@string{+acl1997 = {Proc.\ of the 35th Annual Meeting of the ACL and 8th Conference of the EACL (ACL-EACL'97)}} - -@string{+acl1997ws-ca = {Proc.\ of ACL/EACL'97 Workshop on Natural Language Processing for Communication Aids}} - -@string{+acl1997ws-ie = {Proc.\ of ACL/EACL'97 Workshop on Automatic Information Extraction and Building of Lexical Semantic Resources for NLP Applications}} - -@string{+acl1998 = {Proc.\ of the 36th Annual Meeting of the ACL and 17th International Conference on Computational Linguistics: COLING/ACL-98}} - -@string{+acl1998-ss = {Proc.\ of the 36th Annual Meeting of the ACL and 17th International Conference on Computational Linguistics (COLING/ACL-98), Student Session}} - -@string{+acl1999 = {Proc.\ of the 37th Annual Meeting of the ACL}} - -@string{+acl2000 = {Proc.\ of the 38th Annual Meeting of the ACL}} - -@string{+acl2001 = {Proc.\ of the 39th Annual Meeting of the ACL and 10th Conference of the EACL (ACL-EACL 2001)}} - -@string{+acl2001-ddmt = {Proc.\ of the ACL/EACL 2001 Workshop on Data-Driven Methods in Machine Translation}} - -@string{+acl2001-wscoll = {Proc.\ of the ACL/EACL 2001 Workshop on the Computational Extraction, Analysis and Exploitation of Collocations}} - -@string{+acl2002 = {Proc.\ of the 40th Annual Meeting of the ACL and 3rd Annual Meeting of the NAACL (ACL-2002)}} - -@string{+acl2002-lexacq = {Proc.\ of the ACL-2002 SIGLEX Workshop on Unsupervised Lexical Acquisition}} - -@string{+acl2002-sigphon = {Proc.\ of the 6th Meeting of the ACL Special Interest Group in Computational Phonology}} - -@string{+acl2002-ss = {Proc.\ of the Student Research Workshop, 40th Annual Meeting of the ACL (ACL-2002)}} - -@string{+acl2002-wsd = {Proc.\ of the ACL-2002 Workshop on Word Sense Disambiguation: Recent Successes and Future Directions}} - -@string{+acl2003 = {Proc.\ of the 41st Annual Meeting of the ACL (ACL-2003)}} - -@string{+acl2003-mwe = {Proc.\ of the ACL-2003 Workshop on Multiword Expressions: Analysis, Acquisition and Treatment}} - -@string{+acl2004 = {Proc.\ of the 42nd Annual Meeting of the ACL (ACL-2004)}} - -@string{+acl2004-mwe = {Proc.\ of the ACL 2004 Workshop on Multiword Expressions: Integrating Processing}} - -@string{+acl2004-senseval = {Proc.\ of Senseval-3: Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text}} - -@string{+acl2004-tmi = {Proc.\ of the 2nd Workshop on Text Meaning and Interpretation}} - -@string{+acl2005 = {Proc.\ of the 43rd Annual Meeting of the ACL (ACL-2005)}} - -@string{+acl2005-dla = {Proc.\ of the ACL 2005 Workshop on Deep Lexical Acquisition}} - -@string{+acl2005-pt = {Proc.\ of the ACL 2005 Workshop on Parallel Texts}} - -@string{+acl2006 = {Proc.\ of the 44th Annual Meeting of the ACL and 21st International Conference on Computational Linguistics (COLING/ACL-2006)}} - -@string{+acl2007 = {Proc.\ of the 45th Annual Meeting of the ACL (ACL-2007)}} - -@string{+acl2008 = {Proc.\ of the 46th Annual Conference of the Association for Computational Linguistics: Human Language Technologies (ACL-08:HLT)}} - -@string{+acl2009 = {Proc.\ of the Joint conference of the 47th Annual Meeting of the Association for Computational Linguistics and the 4th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing (ACL/IJCNLP-09)}} - -@string{+amta1998 = {Proc.\ of AMTA'98: Conference of the Association for Machine Translation in the Americas}} - -@string{+amta2002 = {Proc.\ of the 6th Conference of the Association for Machine Translation in the Americas (AMTA)}} - -@string{+anlp1988 = {Proc.\ of the 2nd Conference on Applied Natural Language Processing (ANLP)}} - -@string{+anlp1992 = {Proc.\ of the 3rd Conference on Applied Natural Language Processing (ANLP)}} - -@string{+anlp1994 = {Proc.\ of the 4th Conference on Applied Natural Language Processing (ANLP)}} - -@string{+anlp1997 = {Proc.\ of the 5th Conference on Applied Natural Language Processing (ANLP)}} - -@string{+anlp2000 = {Proc.\ of the 6th Conference on Applied Natural Language Processing (ANLP)}} - -@string{+arpa1993 = {Proc.\ of the ARPA Human Language Technology Workshop}} - -@string{+arpa1994 = {Proc.\ of the ARPA Human Language Technology Workshop}} - -@string{+asialex2003 = {Proc.\ of the Asian Association for Lexicography (ASIALEX 2003)}} - -@string{+bls1988 = {Proc.\ of the 14th Annual Meeting of the Berkeley Linguistics Society}} - -@string{+bls2001 = {Proc.\ of the 27th Annual Meeting of the Berkeley Linguistics Society}} - -@string{+cicling2002 = {Proc.\ of the 3rd International Conference on Intelligent Text Processing and Computational Linguistics (CICLing-2002)}} - -@string{+cicling2003 = {Proc.\ of the 4th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing-2003)}} - -@string{+cl = {Computational Linguistics}} - -@string{+clef2003 = {Working Notes for the CLEF 2003 Workshop}} - -@string{+clin1994 = {Papers from the 4th CLIN Meeting}} - -@string{+clin2000 = {Computational Linguistics in the Netherlands 2000}} - -@string{+clin2003 = {Papers from the 14th Meeting of Computational Linguistics in the Netherlands}} - -@string{+cls1968 = {Papers of the 4th Regional Meeting of the Chicago Linguistics Society}} - -@string{+cls1982 = {Papers of the 18th Regional Meeting of the Chicago Linguistics Society}} - -@string{+cls1988 = {Papers of the 24th Regional Meeting of the Chicago Linguistics Society}} - -@string{+cls1995 = {Papers of the 31st Regional Meeting of the Chicago Linguistics Society}} - -@string{+cluk1999 = {Proc.\ of the 2nd UK Special Interest Group for Computational Linguistics (CLUK2)}} - -@string{+cluk2001 = {Proc.\ of the 4th UK Special Interest Group for Computational Linguistics (CLUK4)}} - -@string{+coe1998 = {Proc.\ of the Kanda University of International Studies Graduate School of Language Sciences Centre of Excellence in Linguistics (COE) International Workshop}} - -@string{+cogsci2000 = {Proc.\ of the 22nd Annual Meeting of the Cognitive Science Society (CogSci 2000)}} - -@string{+coling1980 = {Proc.\ of the 8th International Conference on Computational Linguistics (COLING '80)}} - -@string{+coling1982 = {Proc.\ of the 9th International Conference on Computational Linguistics (COLING '82)}} - -@string{+coling1984 = {Proc.\ of the 10th International Conference on Computational Linguistics (COLING '84)}} - -@string{+coling1986 = {Proc.\ of the 11th International Conference on Computational Linguistics (COLING '86)}} - -@string{+coling1990 = {Proc.\ of the 13th International Conference on Computational Linguistics (COLING '90)}} - -@string{+coling1992 = {Proc.\ of the 14th International Conference on Computational Linguistics (COLING '92)}} - -@string{+coling1994 = {Proc.\ of the 15th International Conference on Computational Linguistics (COLING '94)}} - -@string{+coling1996 = {Proc.\ of the 16th International Conference on Computational Linguistics (COLING '96)}} - -@string{+coling1998 = {Proc.\ of the 36th Annual Meeting of the ACL and 17th International Conference on Computational Linguistics (COLING/ACL-98)}} - -@string{+coling1998-nominals = {Proc.\ of the COLING-ACL'98 Workshop on the Computational Treatment of Nominals}} - -@string{+coling1998-term = {Proc.\ of the COLING-ACL'98 Workshop on Computational Terminology}} - -@string{+coling1998-wordnet = {Proc.\ of the COLING-ACL'98 Workshop on the Usage of {WordNet} in Natural Language Processing Systems}} - -@string{+coling2000 = {Proc.\ of the 18th International Conference on Computational Linguistics (COLING-2000)}} - -@string{+coling2000-semws = {Proc.\ of the COLING 2000 Workshop on Semantic Annotation and Intelligent Content}} - -@string{+coling2002 = {Proc.\ of the 19th International Conference on Computational Linguistics (COLING-2002)}} - -@string{+coling2002-gee = {Proc.\ of the Workshop on Grammar Engineering and Evaluation at the 19th International Conference on Computational Linguistics}} - -@string{+coling2002-mt = {Proc.\ of the COLING-2002 Workshop on Machine Translation in Asia}} - -@string{+coling2004 = {Proc.\ of the 20th International Conference on Computational Linguistics (COLING-2004)}} - -@string{+coling2004-dict = {Proc.\ of the COLING-2004 Workshop on Enhancing and Using Electronic Dictionaries}} - -@string{+coling2004-ml = {Proc.\ of the COLING-2004 Workshop on Multilingual Resources}} - -@string{+coling2006 = {Proc.\ of the 44th Annual Meeting of the ACL and 21st International Conference on Computational Linguistics (COLING/ACL 06)}} - -@string{+coling2008 = {Proc.\ of the 22th International Conference on Computational Linguistics (COLING-2008)}} - 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-@string{+emnlp1997 = {Proc.\ of the 2nd Conference on Empirical Methods in Natural Language Processing (EMNLP-97)}} - -@string{+emnlp1998 = {Proc.\ of the 3rd Conference on Empirical Methods in Natural Language Processing (EMNLP-98)}} - -@string{+emnlp1999 = {Proc.\ of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora (EMNLP/VLC-99)}} - -@string{+emnlp2000 = {Proc.\ of the Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora (EMNLP/VLC-2000)}} - -@string{+emnlp2001 = {Proc.\ of the 6th Conference on Empirical Methods in Natural Language Processing (EMNLP-2001)}} - -@string{+emnlp2002 = {Proc.\ of the 2002 Conference on Empirical Methods in Natural Language Processing (EMNLP-2002)}} - -@string{+emnlp2003 = {Proc.\ of the 2003 Conference on Empirical Methods in Natural Language Processing (EMNLP-2003)}} - -@string{+emnlp2004 = {Proc.\ of the 2004 Conference on Empirical Methods in Natural Language Processing (EMNLP-2004)}} - -@string{+emnlp2005 = {Proc.\ of the 2005 Conference on Empirical Methods in Natural Language Processing (EMNLP-2005)}} - -@string{+emnlp2006 = {Proc.\ of the 2006 Conference on Empirical Methods in Natural Language Processing (EMNLP-2006)}} - -@string{+emnlp2007 = {Proc.\ of the 2007 Conference on Empirical Methods in Natural Language Processing (EMNLP-2007)}} - -@string{+ewnlg1999 = {Proc.\ of the 7th European Workshop on Natural Language Generation (EWNLG'99)}} - -@string{+gl2002 = {Proc.\ of the 1st International Workshop on Generative Approaches to the Lexicon}} - -@string{+gl2003 = {Proc.\ of the 2nd International Workshop on Generative Approaches to the Lexicon}} - -@string{+hlt2001 = {Proc.\ of Human Language Technology (HLT) 2001}} - -@string{+hpsg2002 = {Proc.\ of the 9th International Conference on Head-Driven Phrase Structure Grammar (HPSG-2002)}} - -@string{+hpsg2003 = {Proc.\ of the 10th International Conference on Head-Driven Phrase Structure Grammar (HPSG-2003)}} - -@string{+icml1992 = {Proc.\ of the 9th International Machine Learning Conference}} - -@string{+icml1993 = {Proc.\ of the 10th International Conference on Machine Learning}} - -@string{+icml1994 = {Proc.\ of the 11th International Conference on Machine Learning}} - -@string{+icml1999 = {Proc.\ of the 16th International Conference on Machine Learning}} - -@string{+icslp1992 = {Proc.\ of the 2nd International Conference on Spoken Language Processing (ICSLP'92)}} - -@string{+icslp1996 = {Proc.\ of the 4th International Conference on Spoken Language Processing (ICSLP'96)}} - -@string{+icslp1998 = {Proc.\ of the 5th International Conference on Spoken Language Processing (ICSLP'98)}} - -@string{+ijcai1989 = {Proc.\ of the 11th International Joint Conference on Artificial Intelligence (IJCAI-89)}} - -@string{+ijcai1991 = {Proc.\ of the 12th International Joint Conference on Artificial Intelligence (IJCAI-91)}} - -@string{+ijcai1993 = {Proc.\ of the 13th International Joint Conference on Artificial Intelligence (IJCAI-93)}} - -@string{+ijcai1995 = {Proc.\ of the 14th International Joint Conference on Artificial Intelligence (IJCAI-95)}} - -@string{+ijcai1997 = {Proc.\ of the 15th International Joint Conference on Artificial Intelligence (IJCAI-97)}} - -@string{+ijcai1999 = {Proc.\ of the 16th International Joint Conference on Artificial Intelligence (IJCAI-99)}} - -@string{+ijcnlp2004 = {Proc.\ of the First International Joint Conference on Natural Language Processing (IJCNLP-2004)}} - -@string{+iral2003 = {Proc.\ of the The Sixth International Workshop on Information Retrieval with Asian Languages (IRAL2003)}} - -@string{+iwslt2005 = {Proc.\ of the International Workshop on Spoken Language Translation}} - -@string{+jml = {Journal of Memory and Language}} - -@string{+jnlp = {Journal of Natural Language Processing}} - -@string{+jnlp1996 = {Proc.\ of the 2nd Annual Meeting of the Association for Natural Language Processing (Japan)}} - -@string{+jnlp1998 = {Proc.\ of the 4th Annual Meeting of the Association for Natural Language Processing (Japan)}} - -@string{+jnlp1999 = {Proc.\ of the 5th Annual Meeting of the Association for Natural Language Processing (Japan)}} - -@string{+jnlp2001 = {Proc.\ of the 7th Annual Meeting of the Association for Natural Language Processing (Japan)}} - -@string{+jnlp2002 = {Proc.\ of the 8th Annual Meeting of the Association for Natural Language Processing (Japan)}} - -@string{+jnlp2004 = {Proc.\ of the 10th Annual Meeting of the Association for Natural Language Processing (Japan)}} - -@string{+lrec1998 = {Proc.\ of the 1st International Conference on Language Resources and Evaluation (LREC-98)}} - -@string{+lrec2000 = {Proc.\ of the 2nd International Conference on Language Resources and Evaluation (LREC-2000)}} - -@string{+lrec2002 = {Proc.\ of the 3rd International Conference on Language Resources and Evaluation (LREC-2002)}} - -@string{+lrec2004 = {Proc.\ of the 4th International Conference on Language Resources and Evaluation (LREC-2004)}} - -@string{+lrec2006 = {Proc.\ of the 5th International Conference on Language Resources and Evaluation (LREC-2006)}} - -@string{+lsa = {Proc.\ of the Linguistics Society of America (LSA) Annual Meeting}} - -@string{+ml = {Machine Learning}} - -@string{+mtsummit1997 = {Proc.\ of the Fifth Machine Translation Summit (MT Summit V)}} - -@string{+mtsummit2003 = {Proc.\ of the Ninth Machine Translation Summit (MT Summit IX)}} - -@string{+naacl2000 = {Proc.\ of the 1st Annual Meeting of the North American Chapter of Association for Computational Linguistics (NAACL2000)}} - -@string{+naacl2001 = {Proc.\ of the 2nd Annual Meeting of the North American Chapter of Association for Computational Linguistics (NAACL2001)}} - -@string{+naacl2001-wn = {Proc.\ of the NAACL 2001 Workshop on WordNet and Other Lexical Resources: Applications, Extensions and Customizations}} - -@string{+naacl2002 = {Proc.\ of the 40th Annual Meeting of the ACL and 3rd Annual Meeting of the NAACL (ACL-2002)}} - -@string{+naacl2003 = {Proc.\ of the 3rd International Conference on Human Language Technology Research and 4th Annual Meeting of the NAACL (HLT-NAACL 2003)}} - -@string{+naacl2004 = {Proc.\ of the 4th International Conference on Human Language Technology Research and 5th Annual Meeting of the NAACL (HLT-NAACL 2004)}} - -@string{+naacl2005 = {Proc.\ of the 5th International Conference on Human Language Technology Research and 6th Annual Meeting of the NAACL (HLT-NAACL 2005)}} - -@string{+naacl2006 = {Proc.\ of the 6th International Conference on Human Language Technology Research and 7th Annual Meeting of the NAACL (HLT-NAACL 2006)}} - -@string{+naacl2006-smt = {Proc.\ of the HLT-NAACL 2006 Workshop on Statistical Machine Translation}} - -@string{+naacl2007 = {Proc.\ of the 7th International Conference on Human Language Technology Research and 8th Annual Meeting of the NAACL (HLT-NAACL 2007)}} - -@string{+naacl2007-ssst = {Proc.\ of the HLT-NAACL Workshop on Syntax and Structure in Statistical Translation (SSST 2007)}} - -@string{+nemlap1994 = {Proc.\ of the Conference on New Methods in Natural Language Processing}} - -@string{+nemlap1996 = {Proc.\ of the 2nd International Conference on New Methods in Natural Language Processing}} - -@string{+nemlap1998 = {Proc.\ of the Joint Conference on New Methods in Natural Language Processing and Natural Language Learning (NeMLaP3/CoNLL-98)}} - -@string{+nle = {Natural Language Engineering}} - -@string{+nlprs1995 = {Proc.\ of the 3rd Natural Language Processing Pacific Rim Symposium 1995 (NLPRS'95)}} - -@string{+nlprs1997 = {Proc.\ of the 4th Natural Language Processing Pacific Rim Symposium 1997 (NLPRS'97)}} - -@string{+paclic2000 = {Proc.\ of the 14th Pacific Asia Conference on Language, Information and Computation (PACLIC 14)}} - -@string{+paclic2004 = {Proc.\ of the 18th Pacific Asia Conference on Language, Information and Computation (PACLIC 18)}} - -@string{+pacling2005 = {Proc.\ of the 6th Meeting of the Pacific Association for Computational Linguistics (PACLING-2005)}} - -@string{+papillon2003 = {Proc.\ of the Papillon-2003 Workshop}} - -@string{+papillon2004 = {Proc.\ of the Papillon-2004 Workshop on Multilingual Lexical Databases}} - -@string{+riao1988 = {Proc.\ of Recherche d'Informations Assistee par Ordinateur 1988 (RIAO'88)}} - -@string{+riao2000 = {Proc.\ of Recherche d'Informations Assistee par Ordinateur 2000 (RIAO'2000)}} - -@string{+sigir1990 = {Proc.\ of 13th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'90)}} - -@string{+sigir1993 = {Proc.\ of 16th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'93)}} - -@string{+sigir1994 = {Proc.\ of 17th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'94)}} - -@string{+sigir1995 = {Proc.\ of 18th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'95)}} - -@string{+sigir1996 = {Proc.\ of 19th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'96)}} - -@string{+sigir1997 = {Proc.\ of 20th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'97)}} - -@string{+sigir1998 = {Proc.\ of 21st International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'98)}} - -@string{+sigir1999 = {Proc.\ of 22nd International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR'99)}} - -@string{+sigir2000 = {Proc.\ of 23rd International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2000)}} - -@string{+sigir2001 = {Proc.\ of 24th International ACM-SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2001)}} - -@string{+sigsemprep2003 = {Proc.\ of the ACL-SIGSEM Workshop on the Linguistic Dimensions of Prepositions and their Use in Computational Linguistics Formalisms and Applications}} - -@string{+sigsemprep2005 = {Proc.\ of the Second ACL-SIGSEM Workshop on the Linguistic Dimensions of Prepositions and their Use in Computational Linguistics Formalisms and Applications}} - -@string{+taln1999 = {Actes de la 6e Conf\'erence annuelle sur le Traitement Automatique des Langues Naturelles (TALN '99)}} - -@string{+tmi1993 = {Proc.\ of the 5th International Conference on Theoretical and Methodological Issues in Machine Translation (TMI-93)}} - -@string{+tmi1995 = {Proc.\ of the 6th International Conference on Theoretical and Methodological Issues in Machine Translation (TMI-95)}} - -@string{+tmi1997 = {Proc.\ of the 7th International Conference on Theoretical and Methodological Issues in Machine Translation (TMI-97)}} - -@string{+tmi1999 = {Proc.\ of the 8th International Conference on Theoretical and Methodological Issues in Machine Translation (TMI-99)}} - -@string{+tmi2002 = {Proc.\ of the 9th International Conference on Theoretical and Methodological Issues in Machine Translation (TMI 2002)}} - -@string{+trec1999 = {Proc.\ of the 7th Text REtrieval Conference (TREC-7)}} - -@string{+trec2000 = {Proc.\ of the 8th Text REtrieval Conference (TREC-8)}} - -@string{+wcn1994 = {Proc.\ of the Workshop on Compound Nouns: Multilingual Aspects of Nominal Composition}} - -@string{+wmt2008 = {Proc.\ of the Third Workshop on Machine Translation}} - -@string{+wvlc1993 = {Proc.\ of the Workshop on Very Large Corpora: Academic and Industrial Perspectives}} - -@string{+wvlc1994 = {Proc.\ of the 2nd Annual Workshop on Very Large Corpora}} - -@string{+wvlc1995 = {Proc.\ of the 3rd Annual Workshop on Very Large Corpora}} - -@string{+wvlc1996 = {Proc.\ of the 4th Annual Workshop on Very Large Corpora}} - -@string{+wvlc1997 = {Proc.\ of the 5th Annual Workshop on Very Large Corpora}} - -@string{+wvlc1998 = {Proc.\ of the 6th Annual Workshop on Very Large Corpora}} - -@string{ajcl = {American Journal of Computational Linguistics}} - - -@inbook{klein04hypergraph, - Address = {Norwell, MA, USA}, - Author = {Klein, Dan and Manning, Christopher D.}, - Book = {New developments in parsing technology}, - Date-Added = {2009-11-29 15:52:20 +0000}, - Date-Modified = {2009-11-29 15:52:33 +0000}, - Isbn = {1-4020-2293-X}, - Pages = {351--372}, - Publisher = {Kluwer Academic Publishers}, - Title = {Parsing and hypergraphs}, - Year = {2004}} - -@inproceedings{vangael08beam, - Abstract = {The infinite hidden Markov model is a non-parametric extension of the widely used hidden Markov model. Our paper introduces a new inference algorithm for the infinite Hidden Markov model called beam sampling . Beam sampling combines slice sampling, which limits the number of states considered at each time step to a finite number, with dynamic programming, which samples whole state trajectories efficiently. Our algorithm typically outperforms the Gibbs sampler and is more robust. We present applications of iHMM inference using the beam sampler on changepoint detection and text prediction problems.}, - Address = {New York, NY, USA}, - Author = {Van Gael, Jurgen and Saatci, Yunus and Teh, Yee W. and Ghahramani, Zoubin}, - Booktitle = {ICML '08: Proceedings of the 25th international conference on Machine learning}, - Citeulike-Article-Id = {5943766}, - Citeulike-Linkout-0 = {http://portal.acm.org/citation.cfm?id=1390156.1390293}, - Citeulike-Linkout-1 = {http://dx.doi.org/10.1145/1390156.1390293}, - Date-Added = {2009-11-29 13:51:26 +0000}, - Date-Modified = {2009-11-29 13:51:50 +0000}, - Doi = {10.1145/1390156.1390293}, - Isbn = {978-1-60558-205-4}, - Keywords = {dirichlet-process, mcmc, model, slice-sampling}, - Location = {Helsinki, Finland}, - Pages = {1088--1095}, - Posted-At = {2009-11-12 20:41:25}, - Priority = {2}, - Publisher = {ACM}, - Title = {Beam sampling for the infinite hidden Markov model}, - Url = {http://dx.doi.org/10.1145/1390156.1390293}, - Year = {2008}, - Bdsk-Url-1 = {http://dx.doi.org/10.1145/1390156.1390293}} - -@inproceedings{blunsom09acl, - Address = {Suntec, Singapore}, - Author = {Blunsom, Phil and Cohn, Trevor and Dyer, Chris and Osborne, Miles}, - Booktitle = {Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP}, - Month = {August}, - Pages = {782--790}, - Publisher = {Association for Computational Linguistics}, - Title = {A Gibbs Sampler for Phrasal Synchronous Grammar Induction}, - Url = {http://www.aclweb.org/anthology/P/P09/P09-1088}, - Year = {2009}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/P/P09/P09-1088}} - -@article{neal03slice, - Author = {Radford Neal}, - Date-Added = {2009-11-28 22:31:06 +0000}, - Date-Modified = {2009-11-28 22:32:26 +0000}, - Journal = {Annals of Statistics}, - Pages = {705--767}, - Title = {Slice Sampling}, - Volume = {31}, - Year = {2003}} - -@inproceedings{joshua09, - Address = {Athens, Greece}, - Author = {Zhifei Li and Chris Callison-Burch and Chris Dyer and Sanjeev Khudanpur and Lane Schwartz and Wren Thornton and Jonathan Weese and Omar Zaidan}, - Booktitle = {Proceedings of the Fourth Workshop on Statistical Machine Translation}, - Date-Added = {2009-11-03 12:24:15 +0000}, - Date-Modified = {2009-11-03 12:24:40 +0000}, - Month = {March}, - Pages = {135--139}, - Publisher = {Association for Computational Linguistics}, - Title = {Joshua: An Open Source Toolkit for Parsing-Based Machine Translation}, - Url = {http://www.aclweb.org/anthology/W/W09/W09-0x24}, - Year = {2009}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/W/W09/W09-0x24}} - -@inproceedings{cohn09naacl, - Address = {Morristown, NJ, USA}, - Author = {Cohn, Trevor and Goldwater, Sharon and Blunsom, Phil}, - Booktitle = {NAACL '09: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics on ZZZ}, - Date-Added = {2009-10-30 16:03:09 +0000}, - Date-Modified = {2009-10-30 16:03:18 +0000}, - Isbn = {978-1-932432-41-1}, - Location = {Boulder, Colorado}, - Pages = {548--556}, - Publisher = {Association for Computational Linguistics}, - Title = {Inducing compact but accurate tree-substitution grammars}, - Year = {2009}} - -@inproceedings{blunsom09acl_short, - Address = {Suntec, Singapore}, - Author = {Blunsom, Phil and Cohn, Trevor and Goldwater, Sharon and Johnson, Mark}, - Booktitle = {Proceedings of the ACL-IJCNLP 2009 Conference Short Papers}, - Date-Added = {2009-10-30 15:59:35 +0000}, - Date-Modified = {2009-10-30 15:59:49 +0000}, - Month = {August}, - Pages = {337--340}, - Publisher = {Association for Computational Linguistics}, - Title = {A Note on the Implementation of Hierarchical Dirichlet Processes}, - Url = {http://www.aclweb.org/anthology/P/P09/P09-2085}, - Year = {2009}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/P/P09/P09-2085}} - -@inproceedings{arun09conll, - Address = {Morristown, NJ, USA}, - Author = {Arun, Abhishek and Dyer, Chris and Haddow, Barry and Blunsom, Phil and Lopez, Adam and Koehn, Philipp}, - Booktitle = {CoNLL '09: Proceedings of the Thirteenth Conference on Computational Natural Language Learning}, - Date-Added = {2009-10-30 15:56:30 +0000}, - Date-Modified = {2009-10-30 15:57:33 +0000}, - Isbn = {978-1-932432-29-9}, - Location = {Boulder, Colorado}, - Pages = {102--110}, - Publisher = {Association for Computational Linguistics}, - Title = {Monte carlo inference and maximization for phrase-based translation}, - Year = {2009}} - -@inproceedings{cohn09emnlp, - Address = {Singapore}, - Author = {Cohn, Trevor and Blunsom, Phil}, - Booktitle = {Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing}, - Citeulike-Article-Id = {5427393}, - Citeulike-Linkout-0 = {http://www.aclweb.org/anthology-new/D/D09/D09-1037.bib}, - Citeulike-Linkout-1 = {http://www.aclweb.org/anthology-new/D/D09/D09-1037.pdf}, - Date-Added = {2009-10-30 15:53:43 +0000}, - Date-Modified = {2009-10-30 15:54:28 +0000}, - Keywords = {emnlp2009}, - Month = {August}, - Pages = {352--361}, - Posted-At = {2009-08-12 16:03:51}, - Priority = {2}, - Publisher = {Association for Computational Linguistics}, - Title = {A {Bayesian} Model of Syntax-Directed Tree to String Grammar Induction}, - Url = {http://www.aclweb.org/anthology-new/D/D09/D09-1037.bib}, - Year = {2009}, - Bdsk-File-1 = {YnBsaXN0MDDUAQIDBAUIJidUJHRvcFgkb2JqZWN0c1gkdmVyc2lvblkkYXJjaGl2ZXLRBgdUcm9vdIABqAkKFRYXGyIjVSRudWxs0wsMDQ4RFFpOUy5vYmplY3RzV05TLmtleXNWJGNsYXNzog8QgASABqISE4ACgAOAB1lhbGlhc0RhdGFccmVsYXRpdmVQYXRo0hgNGRpXTlMuZGF0YU8RAfgAAAAAAfgAAgAADE1hY2ludG9zaCBIRAAAAAAAAAAAAAAAAAAAAMarigZIKwAAACDEGhhjb2huLWJsdW5zb20tZW1ubHAwOS5wZGYAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAIMQoxxBqsAAAAAAAAAAAAAMABQAACSAAAAAAAAAAAAAAAAAAAAAEcHVicwAQAAgAAMare/YAAAARAAgAAMcQarAAAAABABwAIMQaACC8VwAgvD0AIFfBAAr3ewAJOnoAAJDnAAIAYU1hY2ludG9zaCBIRDpVc2VyczpwYmx1bnNvbTp3b3Jrc3BhY2U6aG9tZXBhZ2U6Y2xnLm94LmFjLnVrOmJsdW5zb206cHViczpjb2huLWJsdW5zb20tZW1ubHAwOS5wZGYAAA4AMgAYAGMAbwBoAG4ALQBiAGwAdQBuAHMAbwBtAC0AZQBtAG4AbABwADAAOQAuAHAAZABmAA8AGgAMAE0AYQBjAGkAbgB0AG8AcwBoACAASABEABIAVFVzZXJzL3BibHVuc29tL3dvcmtzcGFjZS9ob21lcGFnZS9jbGcub3guYWMudWsvYmx1bnNvbS9wdWJzL2NvaG4tYmx1bnNvbS1lbW5scDA5LnBkZgATAAEvAAAVAAIAD///AACABdIcHR4fWCRjbGFzc2VzWiRjbGFzc25hbWWjHyAhXU5TTXV0YWJsZURhdGFWTlNEYXRhWE5TT2JqZWN0XxBELi4vLi4vLi4vaG9tZXBhZ2UvY2xnLm94LmFjLnVrL2JsdW5zb20vcHVicy9jb2huLWJsdW5zb20tZW1ubHAwOS5wZGbSHB0kJaIlIVxOU0RpY3Rpb25hcnkSAAGGoF8QD05TS2V5ZWRBcmNoaXZlcgAIABEAFgAfACgAMgA1ADoAPABFAEsAUgBdAGUAbABvAHEAcwB2AHgAegB8AIYAkwCYAKACnAKeAqMCrAK3ArsCyQLQAtkDIAMlAygDNQM6AAAAAAAAAgEAAAAAAAAAKAAAAAAAAAAAAAAAAAAAA0w=}} - -@inproceedings{blunsom06question, - Address = {New York, NY, USA}, - Author = {Blunsom, Phil and Kocik, Krystle and Curran, James R.}, - Booktitle = {SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval}, - Date-Added = {2009-10-30 15:26:07 +0000}, - Date-Modified = {2009-10-30 15:26:39 +0000}, - Doi = {http://doi.acm.org/10.1145/1148170.1148282}, - Isbn = {1-59593-369-7}, - Location = {Seattle, Washington, USA}, - Pages = {615--616}, - Publisher = {ACM}, - Title = {Question classification with log-linear models}, - Year = {2006}, - Bdsk-File-1 = {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}} - 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Papineni and S. Roukos and T. Ward and W. Zhu}, - number = {RC22176 (W0109-022)}, - institution = {IBM Research Division, Thomas J. Watson Research Center}, - Title = {Bleu: a method for automatic evaluation of machine translation}, - Url = {citeseer.ist.psu.edu/papineni02bleu.html}, - Year = {2001}, - Bdsk-Url-1 = {citeseer.ist.psu.edu/papineni02bleu.html}} - -@inproceedings{papineni02bleu, - Address = {Philadelphia, Pennsylvania}, - Author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-Jing Zhu}, - Booktitle = +ACL2002, - Pages = {311--318}, - Title = {BLEU: a method for automatic evaluation of machine translation}, - Year = {2002}} - -@article{papineni98dtm, - Author = {Papineni, K.A. and Roukos, S. and Ward, R.T.}, - Journal = {Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on}, - Pages = {189-192 vol.1}, - Title = {Maximum likelihood and discriminative training of direct translation models}, - Volume = {1}, - Year = {12-15 May 1998}} - -@inproceedings{koehn04pharaoh, - Author = {Philipp Koehn}, - Booktitle = {Proc.\ of the AMTA-2004}, - Title = {Pharaoh: a Beam Search Decoder for Phrase-Based Statistical Machine Translation Models}, - Year = {2004}} - -@inproceedings{koehn07moses, - Address = {Prague}, - Author = {Philipp Koehn and Hieu Hoang and Alexandra Birch and Chris Callison-Burch and Marcello Federico and Nicola Bertoldi and Brooke Cowan and Wade Shen and Christine Moran and Richard Zens and Chris Dyer and Ondrej Bojar and Alexandra Constantin and Evan Herbst}, - Booktitle = +ACL2007, - Title = {Moses: Open Source Toolkit for Statistical Machine Translation}, - Year = {2007}} - -@article{bangalore99supertagging, - Author = {Srinivas Bangalore and Aravind K. Joshi}, - Journal = {Computational Linguistics}, - Number = {2}, - Pages = {237-265}, - Title = {Supertagging: An Approach to Almost Parsing}, - Url = {citeseer.ist.psu.edu/bangalore99supertagging.html}, - Volume = {25}, - Year = {1999}, - Bdsk-Url-1 = {citeseer.ist.psu.edu/bangalore99supertagging.html}} - -@inproceedings{hockenmaier02ccgbank, - Address = {Las Palmas, Spain}, - Author = {Julia Hockenmaier and Mark Steedman}, - Booktitle = +LREC2002, - Pages = {1974--1981}, - Title = {Acquiring Compact Lexicalized Grammars from a Cleaner Treebank}, - Url = {citeseer.ist.psu.edu/531192.html}, - Year = {2002}, - Bdsk-Url-1 = {citeseer.ist.psu.edu/531192.html}} - -@inproceedings{Copestake:Flickinger:2000, - Address = {Athens, Greece}, - Author = {Ann Copestake and Dan Flickinger}, - Booktitle = +LREC2000, - Title = {An open-source grammar development environment and broad-coverage {English} grammar using {HPSG}}, - Year = 2000} - -@incollection{Flickinger:2002, - Author = {Dan Flickinger}, - Crossref = {_CollaborativeLangEng}, - Title = {On building a more efficient grammar by exploiting types}} - -@book{_CollaborativeLangEng, - Address = {Stanford, USA}, - Booktitle = {Collaborative Language Engineering}, - Editor = {Stephan Oepen and Dan Flickinger and Jun'ichi Tsujii and Hans Uszkoreit}, - Publisher = {CSLI Publications}, - Title = {Collaborative Language Engineering}, - Year = 2002} - -@inproceedings{Uszkoreit:2002, - Address = {Taipei, Taiwan}, - Author = {Hans Uszkoreit}, - Booktitle = +COLING2002, - Title = {New Chances for Deep Linguistic Processing}, - Year = {2002}} - -@book{Butt+:1999, - Address = {Stanford, USA}, - Author = {Miriam Butt and Tracy {Holloway King} and Maria-Eugenia Nino and Frederique Segond}, - Publisher = {CSLI Publications}, - Title = {A Grammar Writer's Cookbook}, - Year = 1999} - -@inproceedings{Bos+:2004, - Address = {Geneva, Switzerland}, - Author = {Johan Bos and Stephen Clark and Mark Steedman and James R. Curran and Julia Hockenmaier}, - Booktitle = +COLING2004, - Pages = {1240--7}, - Title = {Wide-Coverage Semantic Representations from a {CCG} Parser}, - Year = 2004} - -@inproceedings{vanNoord:2004, - Address = {Barcelona, Spain}, - Author = {Gertjan {van Noord}}, - Booktitle = +ACL2004, - Title = {Error Mining for Wide-Coverage Grammar Engineering}, - Year = 2004} - -@inproceedings{zhang:kordoni:2006, - Address = {Genoa, Italy}, - Author = {Yi Zhang and Valia Kordoni}, - Booktitle = +LREC2006, - Title = {Automated Deep Lexical Acquisition for Robust Open Texts Processing}, - Year = {2006}} - -@inproceedings{zhang-kordoni:2005:ALTA2005, - Address = {Sydney, Australia}, - Author = {Yi Zhang and Valia Kordoni}, - Booktitle = {Proc.\ of the Australasian Language Technology Workshop 2005}, - Pages = {24--31}, - Title = {A Statistical Approach towards Unknown Word Type Prediction for Deep Grammars}, - Year = {2005}} - -@inproceedings{blunsom04srl, - Address = {Sydney, Australia}, - Author = {Phil Blunsom}, - Booktitle = {Proc.\ of the Australasian Language Technology Workshop 2004}, - Pages = {109--116}, - Title = {Maximum Entropy {M}arkov models for semantic role labelling}, - Year = {2005}} - -@inproceedings{blunsom06supertagging, - Address = {Sydney, Australia}, - Author = {Blunsom, Phil and Baldwin, Timothy}, - Booktitle = {Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing}, - Month = {July}, - Pages = {164--171}, - Title = {Multilingual Deep Lexical Acquisition for {HPSG}s via Supertagging}, - Year = {2006}, - Bdsk-File-1 = {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}} - -@inproceedings{Ben:Fli:Oep:02, - Address = {Taipei, Taiwan}, - Author = {Emily M. Bender and Dan Flickinger and Stephan Oepen}, - Booktitle = +COLING2002-GEE, - Title = {The Grammar {M}atrix. {A}n Open-Source Starter-Kit for the Rapid Development of Cross-Linguistically Consistent Broad-Coverage Precision Grammar}, - Year = 2002} - -@inproceedings{Riezler:2002, - Address = {Philadelphia, USA}, - Author = {Stefan Riezler and Tracy H. King and Ronald M. Kaplan and Richard Crouch and John T. {Maxwell III} and Mark Johnson}, - Booktitle = +ACL2002, - Title = {Parsing the {Wall Street Journal} using a {Lexical-Functional Grammar} and Discriminative Estimation Techniques}, - Year = 2002} - -@incollection{Baldwin+:2005b, - Author = {Timothy Baldwin and Emily M. Bender and Dan Flickinger and Ara Kim and Stephan Oepen}, - Crossref = {_Kepser:Reis:2005}, - Title = {Beauty and the Beast: What running a broad-coverage precision grammar over the {BNC} taught us about the grammar --- and the corpus}} - -@inproceedings{Baldwin:2005d, - Address = {Ann Arbor, USA}, - Author = {Timothy Baldwin}, - Booktitle = +ACL2005-DLA, - Pages = {67--76}, - Title = {Bootstrapping Deep Lexical Resources: Resources for Courses}, - Year = 2005} - -@inproceedings{Baldwin:2005e, - Address = {Tokyo, Japan}, - Author = {Timothy Baldwin}, - Booktitle = +PACLING2005, - Note = {(Invited Paper)}, - Pages = {23--32}, - Title = {General-Purpose Lexical Acquisition: Procedures, Questions and Results}, - Year = {2005}} - -@phdthesis{Fouvry:2003b, - Author = {Frederik Fouvry}, - School = {University of Essex}, - Title = {Robust Processing for Constraint-based Grammar Formalisms}, - Year = 2003} - -@inproceedings{Lapata:Keller:04, - Address = {Boston, USA}, - Author = {Mirella Lapata and Frank Keller}, - Booktitle = +NAACL2004, - Pages = {121--8}, - Title = {The Web as a Baseline: Evaluating the Performance of Unsupervised Web-based Models for a Range of {NLP} Tasks}, - Year = {2004}} - -@phdthesis{Korhonen:2002, - Author = {Anna Korhonen}, - School = {University of Cambridge}, - Title = {Subcategorization Acquisition}, - Year = 2002} - -@inproceedings{Joanis:2003, - Address = {Budapest, Hungary}, - Author = {Eric Joanis and Suzanne Stevenson}, - Booktitle = +EACL2003, - Pages = {163--70}, - Title = {A general feature space for automatic verb classification}, - Year = 2003} - -@book{Pollard:Sag:1994, - Address = {Chicago, USA}, - Author = {Carl Pollard and Ivan A. 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Manning}, - Booktitle = {Proc.\ of The First Workshop on Treebanks and Linguistic Theories (TLT-2002)}, - Title = {{LinGO Redwoods}: A Rich and Dynamic Treebank for {HPSG}}, - Year = 2002} - -@inproceedings{Bond+:2004, - Address = {Hainan Island, China}, - Author = {Francis Bond and Sanae Fujita and Chikara Hashimoto and Kaname Kasahara and Shigeko Nariyama and Eric Nichols and Akira Ohtani and Takaaki Tanaka and Shigeaki Amano}, - Booktitle = +IJCNLP2004, - Pages = {554--9}, - Title = {The {Hinoki} Treebank: A Treebank for Text Understanding}, - Year = 2004} - -@techreport{Matsumoto+:2003, - Author = {Yuji Matsumoto and Akira Kitauchi and Tatsuo Yamashita and Yoshitaka Hirano and Hiroshi Matsuda and Kazuma Takaoka and Masayuki Asahara}, - Institution = {NAIST}, - Title = {{\it Japanese Morphological Analysis System {ChaSen} Version 2.3.3 Manual}}, - Year = 2003} - -@inproceedings{Ngai:Florian:2001, - Address = {Pittsburgh, USA}, - Author = {Grace Ngai and Radu Florian}, - Booktitle = +NAACL2001, - Pages = {40--7}, - Title = {Transformation-based learning in the fast lane}, - Year = 2001} - -@book{vapnik95, - Address = {New York, NY, USA}, - Author = {Vladimir N. 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Oepen}, - Booktitle = {In First Workshop on Treebanks and Linguistic Theories (TLT-2002)}, - Pages = {253--263}, - Title = {Parse disambiguation for a rich {HPSG} grammar}, - Url = {citeseer.ist.psu.edu/toutanova02parse.html}, - Year = {2002}, - Bdsk-Url-1 = {citeseer.ist.psu.edu/toutanova02parse.html}} - -@inproceedings{ninomiya-EtAl:2006:EMNLP, - Address = {Sydney, Australia}, - Author = {Ninomiya, Takashi and Matsuzaki, Takuya and Tsuruoka, Yoshimasa and Miyao, Yusuke and Tsujii, Jun'ichi}, - Booktitle = +EMNLP2006, - Month = {July}, - Pages = {155--163}, - Title = {Extremely Lexicalized Models for Accurate and Fast {HPSG} Parsing}, - Url = {http://www.aclweb.org/anthology/W/W06/W06-1619}, - Year = {2006}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/W/W06/W06-1619}} - -@techreport{nist01, - Author = {NIST}, - Institution = {NIST}, - Title = {Automatic evaluation of machine translation quality using n-gram co-occurrence statistics}, - Type = {technical report}, - Url = {http://www.nist.gov/speech/tests/mt/}, - Year = 2001, - Bdsk-Url-1 = {http://www.nist.gov/speech/tests/mt/}} - -@inproceedings{och02me, - Address = {Philadelphia, USA}, - Author = {Franz Josef Och and Hermann Ney}, - Booktitle = +ACL2002, - Pages = {295--302}, - Title = {Discriminative training and maximum entropy models for statistical machine translation}, - Year = {2002}} - -@inproceedings{och03mert, - Address = {Sapporo, Japan}, - Author = {Franz Josef Och}, - Booktitle = +ACL2003, - Pages = {160--167}, - Title = {Minimum error rate training in statistical machine translation}, - Year = {2003}} - -@inproceedings{joachims06perf, - Address = {Philadelphia, PA, USA}, - Author = {Thorsten Joachims}, - Booktitle = {KDD '06: Proceedings of the 12th ACM SIGKDD international conference on knowledge discovery and data mining}, - Doi = {http://doi.acm.org/10.1145/1150402.1150429}, - Isbn = {1-59593-339-5}, - Pages = {217--226}, - Title = {Training linear {SVM}s in linear time}, - Year = {2006}, - Bdsk-Url-1 = {http://doi.acm.org/10.1145/1150402.1150429}} - -@inproceedings{curran2006multi, - Address = {Sydney, Australia}, - Author = {Curran, James R. and Clark, Stephen and Vadas, David}, - Booktitle = +ACL2006, - Month = {July}, - Pages = {697--704}, - Title = {Multi-Tagging for Lexicalized-Grammar Parsing}, - Url = {http://www.aclweb.org/anthology/P/P06/P06-1088}, - Year = {2006}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/P/P06/P06-1088}} - -@article{rabiner90hmm, - Address = {San Francisco, CA, USA}, - Author = {Lawrence R. 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Peng and A. McCallum}, - Booktitle = +NAACL2004, - Pages = {329--336}, - Title = {Accurate information extraction from research papers using conditional random fields}, - Url = {citeseer.ist.psu.edu/peng04accurate.html}, - Year = {2004}, - Bdsk-Url-1 = {citeseer.ist.psu.edu/peng04accurate.html}} - -@inproceedings{cohn05srl, - Address = {Ann Arbor, Michigan}, - Author = {Cohn, Trevor and Blunsom, Philip}, - Booktitle = +CONLL2005, - Month = {June}, - Pages = {169--172}, - Title = {Semantic Role Labelling with Tree Conditional Random Fields}, - Url = {http://www.aclweb.org/anthology/W/W05/W05-0622}, - Year = {2005}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/W/W05/W05-0622}} - -@inproceedings{blunsom06wa, - Address = {Sydney, Australia}, - Author = {Blunsom, Phil and Cohn, Trevor}, - Booktitle = +ACL2006, - Month = {July}, - Pages = {65--72}, - Title = {Discriminative Word Alignment with Conditional Random Fields}, - Url = {http://www.aclweb.org/anthology/P/P06/P06-1009}, - Year = {2006}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/P/P06/P06-1009}} - -@inproceedings{blunsom08latent, - Address = {Columbus, Ohio}, - Author = {Blunsom, Phil and Cohn, Trevor and Osborne, Miles}, - Booktitle = +ACL2008, - Month = {June}, - Pages = {200--208}, - Title = {A Discriminative Latent Variable Model for Statistical Machine Translation}, - Url = {http://www.aclweb.org/anthology/P/P08/P08-1024}, - Year = {2008}, - Bdsk-File-1 = {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}} - -@inproceedings{blunsom08bscfg, - Address = {Vancouver, Canada}, - Author = {Blunsom, Phil and Cohn, Trevor and Osborne, Miles}, - Booktitle = {Proceedings of NIPS 21}, - Month = {December}, - Title = {Bayesian Synchronous Grammar Induction}, - Year = {2008}, - Bdsk-File-1 = {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}} - -@inproceedings{blunsom08inference, - Address = {Honolulu, Hawaii}, - Author = {Blunsom, Phil and Osborne, Miles}, - Booktitle = {Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing}, - Month = {October}, - Pages = {215--223}, - Title = {Probabilistic Inference for Machine Translation}, - Year = {2008}, - Bdsk-File-1 = {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}} - -@inproceedings{blunsom09gibbs, - Address = {Singapore}, - Author = {Blunsom, Phil and Cohn, Trevor and Dyer, Chris and Osborne, Miles}, - Booktitle = +ACL2009, - Month = {August}, - Title = {A {G}ibbs Sampler for Phrasal Synchronous Grammar Induction}, - Year = {2009}, - Bdsk-File-1 = {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}} - 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Goodman}, - Isbn = {0-591-85426-0}, - Note = {Adviser-Stuart Shieber}, - Order_No = {AAI9832377}, - Publisher = {Harvard University}, - Title = {Parsing inside-out}, - Year = {1998}} - -@inproceedings{mi08forest, - Address = {Columbus, Ohio}, - Author = {Mi, Haitao and Huang, Liang and Liu, Qun}, - Booktitle = +ACL2008, - Month = {June}, - Pages = {192--199}, - Title = {Forest-Based Translation}, - Url = {http://www.aclweb.org/anthology/P/P08/P08-1023}, - Year = {2008}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/P/P08/P08-1023}} - -@inproceedings{huang06syntax, - Address = {Boston, MA}, - Author = {Huang, Liang and Knight, Kevin and Joshi, Aravind}, - Booktitle = {In Proceedings of the 7th Biennial Conference of the Association for Machine Translation in the Americas ({AMTA})}, - Title = {Statistical Syntax-Directed Translation with Extended Domain of Locality}, - Year = {2006}} - -@inproceedings{kumar04mbr, - Author = {Shankar Kumar and William Byrne}, - Booktitle = +NAACL2004, - Pages = {169--176}, - Title = {Minimum bayes-risk decoding for statistical machine translation}, - Year = {2004}} - -@inproceedings{zhang08bitg, - Address = {Columbus, Ohio}, - Author = {Zhang, Hao and Quirk, Chris and Moore, Robert C. and Gildea, Daniel}, - Booktitle = +ACL2008, - Month = {June}, - Pages = {97--105}, - Title = {{Bayesian} Learning of Non-Compositional Phrases with Synchronous Parsing}, - Year = {2008}} - -@inproceedings{newman07distributed, - Author = {David Newman and Arthur Asuncion and Padhraic Smyth and Max Welling}, - Booktitle = {NIPS}, - Publisher = {MIT Press}, - Title = {Distributed Inference for Latent Dirichlet Allocation.}, - Year = {2007}} - -@inproceedings{asuncion08asynchronous, - Author = {Arthur Asuncion and Padhraic Smyth and Max Welling}, - Booktitle = {NIPS}, - Publisher = {MIT Press}, - Title = {Asynchronous Distributed Learning of Topic Models.}, - Year = {2008}} - -@inproceedings{johnson07, - Address = {Rochester, New York}, - Author = {Johnson, Mark and Griffiths, Thomas and Goldwater, Sharon}, - Booktitle = +NAACL2007, - Month = {April}, - Pages = {139--146}, - Title = {{Bayesian} Inference for {PCFG}s via {Markov} Chain {Monte} {Carlo}}, - Url = {http://www.aclweb.org/anthology/N/N07/N07-1018}, - Year = {2007}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/N/N07/N07-1018}} - -@inproceedings{johnson07pos, - Address = {Prague, Czech Republic}, - Author = {Johnson, Mark}, - Booktitle = +EMNLP2007, - Pages = {296--305}, - Title = {Why Doesnt {EM} Find Good {HMM} {POS}-Taggers?}, - Year = {2007}} - -@inproceedings{denero08complexity, - Address = {Columbus, Ohio}, - Author = {DeNero, John and Klein, Dan}, - Booktitle = {Proceedings of ACL-08: HLT, Short Papers}, - Month = {June}, - Pages = {25--28}, - Publisher = {Association for Computational Linguistics}, - Title = {The Complexity of Phrase Alignment Problems}, - Url = {http://www.aclweb.org/anthology/P/P08/P08-2007}, - Year = {2008}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/P/P08/P08-2007}} - -@inproceedings{denero08sampling, - Address = {Honolulu, Hawaii}, - Author = {DeNero, John and Bouchard-C\^{o}t\'{e}, Alexandre and Klein, Dan}, - Booktitle = {Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing}, - Month = {October}, - Pages = {314--323}, - Publisher = {Association for Computational Linguistics}, - Title = {Sampling Alignment Structure under a {B}ayesian Translation Model}, - Url = {http://www.aclweb.org/anthology/D08-1033}, - Year = {2008}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/D08-1033}} - -@inproceedings{birch06constraining, - Address = {New York City}, - Author = {Birch, Alexandra and Callison-Burch, Chris and Osborne, Miles and Koehn, Philipp}, - Booktitle = {Proceedings on the Workshop on Statistical Machine Translation}, - Month = {June}, - Pages = {154--157}, - Publisher = {Association for Computational Linguistics}, - Title = {Constraining the Phrase-Based, Joint Probability Statistical Translation Model}, - Url = {http://www.aclweb.org/anthology/W/W06/W06-3123}, - Year = {2006}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/W/W06/W06-3123}} - -@inproceedings{chang08chinese, - Address = {Prague, Czech Republic}, - Author = {Chang, Pi-Chuan and Jurafsky, Dan and Manning, Christopher D.}, - Booktitle = +WMT2008, - Month = {June}, - Title = {Optimizing {C}hinese Word Segmentation for Machine Translation Performance}, - Year = {2008}} - -@inproceedings{habash06preprocessing, - Address = {New York City}, - Author = {Habash, Nizar and Sadat, Fatiha}, - Booktitle = +NAACL2006, - Publisher = {Association for Computational Linguistics}, - Title = {Arabic Preprocessing Schemes for Statistical Machine Translation}, - Year = {2006}} - -@inproceedings{goldwater07, - Address = {Prague, Czech Republic}, - Author = {Goldwater, Sharon and Griffiths, Tom}, - Booktitle = +ACL2007, - Month = {June}, - Pages = {744--751}, - Title = {A fully Bayesian approach to unsupervised part-of-speech tagging}, - Url = {http://www.aclweb.org/anthology/P/P07/P07-1094}, - Year = {2007}, - Bdsk-Url-1 = {http://www.aclweb.org/anthology/P/P07/P07-1094}} - -@inproceedings{goldwater06, - Address = {Sydney}, - Author = {Goldwater, Sharon and Griffiths, Tom and Johnson, Mark}, - Booktitle = +ACL2006, - Title = {Contextual Dependencies in Unsupervised Word Segmentation}, - Year = {2006}} - -@incollection{goldwater06interpolating, - Address = {Cambridge, MA}, - Author = {Sharon Goldwater and Tom Griffiths and Mark Johnson}, - Booktitle = {Advances in Neural Information Processing Systems 18}, - Editor = {Y. Weiss and B. Sch\"{o}lkopf and J. Platt}, - Pages = {459--466}, - Publisher = {MIT Press}, - Title = {Interpolating between types and tokens by estimating power-law generators}, - Year = {2006}} - -@inproceedings{zhang08factorisation, - Address = {Manchester, UK}, - Author = {Zhang, Hao and Gildea, Daniel and Chiang, David}, - Booktitle = +COLING2008, - Pages = {1081--1088}, - Title = {Extracting Synchronous Grammar Rules From Word-Level Alignments in Linear Time}, - Year = {2008}} - -@article{antoniak74, - Author = {Antoniak, Charles E.}, - Journal = {The Annals of Statistics}, - Number = {6}, - Pages = {1152--1174}, - Title = {Mixtures of Dirichlet Processes with Applications to Bayesian Nonparametric Problems}, - Volume = {2}, - Year = {1974}} - -@phdthesis{blunsom07thesis, - Author = {Blunsom, Phil}, - School = {Department of Computer Science and Software Engineering, The University of Melbourne}, - Title = {Structured Classification for Multilingual Natural Language Processing}, - Year = {2007}} - -@phdthesis{RL:1, - Address = {Stanford, California}, - Author = {R. 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Bottou}, - Pages = {161--168}, - Title = {Bayesian Synchronous Grammar Induction}, - Year = {2009}, - Bdsk-File-1 = {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}} - -@inproceedings{zhang06synchronous, - Author = {Zhang,, Hao and Huang,, Liang and Gildea,, Daniel and Knight,, Kevin}, - Booktitle = +NAACL2006, - Location = {New York, New York}, - Pages = {256--263}, - Title = {Synchronous binarization for machine translation}, - Year = {2006}} - -@article{fraser07measuring, - Address = {Cambridge, MA, USA}, - Author = {Fraser, Alexander and Marcu, Daniel}, - Issn = {0891-2017}, - Journal = {Computational Linguistics}, - Number = {3}, - Pages = {293--303}, - Publisher = {MIT Press}, - Title = {Measuring Word Alignment Quality for Statistical Machine Translation}, - Volume = {33}, - Year = {2007}} - -@inproceedings{teh06, - Author = {Y. Teh}, - Booktitle = {Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics}, - Pages = {985-992}, - Title = {A Hierarchical {B}ayesian Language Model based on {P}itman-{Y}or Processes}, - Year = {2006}} - -@article{ferguson73, - Author = {S. Ferguson}, - Journal = {Annals of Statistics}, - Pages = {209--230}, - Title = {A {Bayesian} Analysis of Some Nonparametric Problems}, - Volume = 1, - Year = 1973} diff --git a/report/pyp_clustering/acl09-short/hdp.aux b/report/pyp_clustering/acl09-short/hdp.aux deleted file mode 100644 index b6bb09aa..00000000 --- a/report/pyp_clustering/acl09-short/hdp.aux +++ /dev/null @@ -1,25 +0,0 @@ -\relax -\citation{goldwater06} -\citation{teh06hdp,goldwater06,goldwater06interpolating,liang07hdppcfg,finkel07infinite,denero08sampling} -\citation{ferguson73} -\citation{teh06hdp} -\citation{goldwater06} -\citation{aldous85} -\citation{antoniak74} -\citation{antoniak74} -\providecommand*\caption@xref[2]{\@setref\relax\@undefined{#1}} -\newlabel{fig:tables}{{1}{2}} -\newlabel{eqn:crp}{{1}{2}} -\newlabel{eq:hdp_p1}{{2}{2}} -\newlabel{fig:graphs}{{2}{2}} -\newlabel{eqn:true_expected}{{3}{2}} -\newlabel{eqn:antoniak_approximation}{{4}{2}} -\citation{antoniak74} -\citation{teh06hdp} -\newlabel{eqn:harmonic}{{5}{3}} -\newlabel{eqn:digamma}{{7}{3}} -\newlabel{fig:histogram}{{3}{3}} -\bibstyle{scrunchacl} -\bibdata{standard} -\newlabel{alg:increment}{{1}{4}} -\newlabel{alg:decrement}{{2}{4}} diff --git a/report/pyp_clustering/acl09-short/hdp.log b/report/pyp_clustering/acl09-short/hdp.log deleted file mode 100644 index b2e019f5..00000000 --- a/report/pyp_clustering/acl09-short/hdp.log +++ /dev/null @@ -1,638 +0,0 @@ -This is pdfTeXk, Version 3.1415926-1.40.9 (Web2C 7.5.7) (format=pdflatex 2008.12.28) 2 DEC 2009 19:45 -entering extended mode - 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E -xpected - [] - - -Underfull \hbox (badness 1275) in paragraph at lines 205--207 -\OT1/ptm/m/n/10.95 Antoniak also gives an approx-i-ma-tion to this - [] - - -LaTeX Warning: Citation `antoniak74' on page 2 undefined on input line 211. - - -LaTeX Warning: Reference `eqn:antoniak_approximation' on page 2 undefined on in -put line 211. - - -LaTeX Warning: Reference `fig:graphs' on page 2 undefined on input line 212. - -[2 <./tables.pdf> <./approximations.pdf>] - -LaTeX Warning: Reference `eqn:antoniak_approximation' on page 3 undefined on in -put line 216. - - -LaTeX Warning: Reference `eqn:true_expected' on page 3 undefined on input line -216. - - -LaTeX Warning: Reference `eqn:true_expected' on page 3 undefined on input line -216. - - -Overfull \hbox (9.47058pt too wide) detected at line 226 - []$[] \OML/cmm/m/it/10.95 E\OT1/cmr/m/n/10.95 [\OML/cmm/m/it/10.95 t[]\ -OT1/cmr/m/n/10.95 ] \OMS/cmsy/m/n/10.95 ^^Y \OML/cmm/m/it/10.95 []P[]\OT1/cmr/ -m/n/10.95 (\OML/cmm/m/it/10.95 w\OT1/cmr/m/n/10.95 )[]\OML/cmm/m/it/10.95 H[] \ -OMS/cmsy/m/n/10.95 ^^@ []$ - [] - - -Underfull \hbox (badness 10000) in paragraph at lines 226--228 -\OT1/ptm/m/n/10.95 We then use the asymp-totic expan-sion, - [] - - -Underfull \hbox (badness 3780) in paragraph at lines 226--228 -[]\OT1/ptm/m/n/10.95 , omit-ing trail-ing terms - [] - - -Overfull \hbox (7.89845pt too wide) detected at line 231 -[] - [] - - -LaTeX Warning: Citation `antoniak74' on page 3 undefined on input line 233. - - -LaTeX Warning: Reference `eqn:harmonic' on page 3 undefined on input line 236. - - -LaTeX Warning: Reference `eqn:digamma' on page 3 undefined on input line 236. - - -LaTeX Warning: Reference `eqn:true_expected' on page 3 undefined on input line -236. - - -LaTeX Warning: Reference `eqn:true_expected' on page 3 undefined on input line -250. - - -LaTeX Warning: Reference `eqn:digamma' on page 3 undefined on input line 250. - - -LaTeX Warning: Reference `fig:graphs' on page 3 undefined on input line 250. - - -LaTeX Warning: Reference `eqn:digamma' on page 3 undefined on input line 250. - - -LaTeX Warning: Citation `teh06hdp' on page 3 undefined on input line 256. - - -LaTeX Warning: Reference `fig:histogram' on page 3 undefined on input line 258. - - - -LaTeX Warning: Reference `fig:tables' on page 3 undefined on input line 258. - - -Overfull \hbox (4.42407pt too wide) in paragraph at lines 264--275 -[][] - [] - - -LaTeX Warning: Reference `fig:tables' on page 3 undefined on input line 276. - - -LaTeX Warning: Reference `fig:tables' on page 3 undefined on input line 276. - - -LaTeX Warning: Reference `fig:histogram' on page 3 undefined on input line 281. - - - -LaTeX Warning: Reference `fig:tables' on page 3 undefined on input line 281. - -[3] - -LaTeX Warning: Reference `alg:increment' on page 4 undefined on input line 283. - - - -LaTeX Warning: Reference `alg:decrement' on page 4 undefined on input line 283. - - - -Underfull \hbox (badness 10000) in paragraph at lines 283--283 -[][]\OT1/ptm/m/n/9 A C++ tem-plate class that imple-ments - [] - - -Underfull \hbox (badness 10000) in paragraph at lines 283--283 -\OT1/ptm/m/n/9 the algo-rithm pre-sented is made avail-able at: - [] - - -LaTeX Warning: Reference `alg:increment' on page 4 undefined on input line 284. - - - -LaTeX Warning: Reference `alg:decrement' on page 4 undefined on input line 284. - - - -LaTeX Warning: Reference `eqn:digamma' on page 4 undefined on input line 348. - - -LaTeX Warning: Reference `fig:graphs' on page 4 undefined on input line 353. - - -Underfull \hbox (badness 2261) in paragraph at lines 353--354 -\OT1/ptm/m/n/10.95 The authors would like to thank Tom Grif- - [] - - -Underfull \hbox (badness 1436) in paragraph at lines 353--354 -\OT1/ptm/m/n/10.95 fiths for pro-vid-ing the code used to pro-duce - [] - -No file hdp.bbl. -[4] (./hdp.aux) - -LaTeX Font Warning: Some font shapes were not available, defaults substituted. - - -LaTeX Warning: There were undefined references. - - -LaTeX Warning: Label(s) may have changed. 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- - -\title{A Note on the Implementation of \\ Hierarchical Dirichlet Processes} - -\author{ - Phil Blunsom$^*$\\\vspace{6pt} pblunsom@inf.ed.ac.uk\\ - {\bf Sharon Goldwater$^*$}\\ sgwater@inf.ed.ac.uk - \And - Trevor Cohn$^*$\\\vspace{6pt} tcohn@inf.ed.ac.uk\\ - {\bf Mark Johnson$^\textrm{\textdagger}$}\\ mark\_johnson@brown.edu - \AND - {\rm $^*$Department of Informatics}\\ - University of Edinburgh\\ - Edinburgh, EH8 9AB, UK \And - {\rm $^\textrm{\textdagger}$Department of Cognitive and Linguistic Sciences}\\ - Brown University \\ - Providence, RI, USA -} -\date{} - -\begin{document} -\maketitle - -% have to come after begin document -%\setlength{\parskip}{0mm} -\setlength{\abovedisplayskip}{1ex} -\setlength{\belowdisplayskip}{1ex} - -\begin{abstract} -The implementation of collapsed Gibbs samplers for non-parametric Bayesian models is non-trivial, requiring considerable book-keeping. -\newcite{goldwater06} presented an approximation which significantly reduces the storage and computation overhead, but we show here that their formulation was incorrect and, even after correction, is grossly inaccurate. -%Efficient implementation is of paramount importance for Gibbs samplers, but this is non-trivial for hierarchical Dirichlet process (HDP) models, which require considerable book-keeping. -%\newcite{goldwater06} presented an approximation which considerably reduces the storage and computation overhead, but we show here that their formulation was incorrect and even after correction is often grossly inaccurate. -We present an alternative formulation which is exact and can be computed easily. -However this approach does not work for hierarchical models, for which case we present an efficient data structure which has a better space complexity than the naive approach. -\end{abstract} - -\section{Introduction} -Unsupervised learning of natural language is one of the most challenging areas in NLP. -Recently, methods from nonparametric Bayesian statistics have been gaining popularity as a way to approach unsupervised learning for a variety of tasks, including language modeling, word and morpheme segmentation, parsing, and machine translation \cite{teh06hdp,goldwater06,goldwater06interpolating,liang07hdppcfg,finkel07infinite,denero08sampling}. %,blunsom08bscfg}. -These models are often based on the Dirichlet process (DP) \cite{ferguson73} or hierarchical Dirichlet process (HDP) \cite{teh06hdp}, with Gibbs sampling as a method of inference. -Exact implementation of such sampling methods requires considerable bookkeeping of various counts, which motivated \newcite{goldwater06} (henceforth, GGJ06) to develop an approximation using expected counts. -However, we show here that their approximation is flawed in two respects: 1) It omits an important factor in the expectation, and 2) Even after correction, the approximation is poor for hierarchical models, which are commonly used for NLP applications. -We derive an improved -$\mathcal{O}(1)$ formula that gives exact values for the expected counts in non-hierarchical models. For hierarchical models, where our formula is not exact, -% approximation formula and show that it follows empirical values much more tightly in a wider variety of settings. For settings in which the approximation is inappropriate, -we present an efficient method for sampling from the HDP (and related -models, such as the hierarchical Pitman-Yor process) that considerably decreases -the memory footprint of such models as compared to the naive -implementation. - -As we have noted, the issues described in this paper apply to models for various kinds of NLP tasks; for concreteness, we will focus on $n$-gram language modeling for the remainder of the paper, closely following the presentation in GGJ06. - -\vspace{-0.05in} -\section{The Chinese Restaurant Process} -GGJ06 present two nonparametric Bayesian language models: a DP unigram -model and an HDP bigram model. Under the DP model, words in a corpus -$\mathbf{w} = w_1 \ldots w_n$ are generated as follows: -\begin{align} -\nonumber G | & \alpha_0, P_0 & \sim & ~ \mbox{DP}(\alpha_0,P_0) \\ -\nonumber w_i | & G & \sim & ~ G -\end{align} -where $G$ is a distribution over an infinite set of possible words, -$P_0$ (the {\em base distribution} of the DP) determines the -probability that an item will be in the support of $G$, and $\alpha_0$ -(the {\em concentration parameter}) determines the variance of $G$. - -One way of understanding the predictions that the DP model makes is through the Chinese restaurant process (CRP) -\cite{aldous85}. -In the CRP, customers (word tokens $w_i$) enter a restaurant with an infinite number of tables and choose a seat. -The table chosen by the $i$th customer, $z_i$, follows the distribution: -\begin{align} -\nonumber P(z_i = k | \mathbf{z}_{-i}) = \left\{ -\begin{array}{ll} - \frac{n_k^{\mathbf{z}_{-i}}}{i - 1 + \alpha_0}, 0 \leq k < K(\mathbf{z}_{-i}) \\ - \frac{\alpha_0}{i - 1 + \alpha_0}, k = K(\mathbf{z}_{-i}) -\end{array} \right. -\label{eqn:crp} -\end{align} -where $\mathbf{z}_{-i} = z_1 \dots z_{i-1}$ are the table assignments of the previous customers, $n_k^{\mathbf{z}_{-i}}$ is the number of customers at table $k$ in ${\mathbf{z}_{-i}}$, and $K(\mathbf{z}_{-i})$ is -the total number of occupied tables. -If we further assume that table $k$ is labeled with a word type $\ell_k$ drawn from $P_0$, then the assignment of tokens to tables defines a distribution over words, with $w_i = \ell_{z_i}$. -See Figure \ref{fig:tables} for an example seating arrangement. - -\begin{figure} -\begin{center} -\includegraphics[width=1.0\columnwidth]{tables.pdf} -\end{center} -\caption[]{A seating assignment describing the state of a unigram CRP. Letters and numbers uniquely identify customers and tables. Note that multiple tables may share a label.} -\label{fig:tables} -\end{figure} - - -Using this model, the predictive probability of $w_i$, conditioned on -the previous words, can be found by summing over possible seating -assignments for $w_i$, and is given by -\begin{align} -P(w_i = w | \mathbf{w}_{-i}) = \frac{n_{w}^{\mathbf{w}_{-i}} + \alpha_0 P_0}{i-1 + \alpha_0} -\end{align} -This prediction turns out to be exactly that of the DP model after integrating out the distribution $G$. -Note that as long as the base distribution $P_0$ is fixed, predictions do not depend on the seating arrangement $\mathbf{z}_{-i}$, only on the count of word $w$ in the previously observed words ($n_{w}^{\mathbf{w}_{-i}}$). -However, in many situations, we may wish to estimate the base distribution itself, creating a {\em hierarchical} model. -Since the base distribution generates table labels, estimates of this distribution are based on the counts of those labels, i.e., the number of tables associated with each word type. - -An example of such a hierarchical model is the HDP bigram model of -GGJ06, in which each word type $w$ is associated with its own -restaurant, where customers in that restaurant correspond to words -that follow $w$ in the corpus. All the bigram restaurants share a -common base distribution $P_1$ over unigrams, which must be inferred. -Predictions in this model are as follows: -\begin{align} -\small -\nonumber P_2(w_i | \mathbf{h}_{-i}) &= \frac{n_{(w_{i-1},w_i)}^{\mathbf{h_{-i}}} + \alpha_1 P_1(w_i | \mathbf{h}_{-i})}{n_{(w_{i-1}, *)}^{\mathbf{h_{-i}}} + \alpha_1} \\ - P_1(w_i | \mathbf{h}_{-i}) &= %\left\{ - \frac{t_{w_i}^{\mathbf{h_{-i}}} + \alpha_0 P_0(w_i)}{t_*^{\mathbf{h_{-i}}} + \alpha_0} \label{eq:hdp_p1} -%\begin{array}{ll} -% \frac{t_{\Sigma*} + \frac{\tau}{2}}{t + \tau} \frac{t_{w_i} + \alpha_0 P_0(w_i)}{t_{\Sigma*} + \alpha_0}, w_i \in \Sigma* -% \frac{t_{\Sigma*} + \frac{\tau}{2}}{t + \tau}, w_i = \$ -%\end{array} \right. -\end{align} -where $\mathbf{h}_{-i} = (\mathbf{w}_{-i}, \mathbf{z}_{-i})$, $t_{w_i}^{\mathbf{h_{-i}}}$ is the number of tables labelled with $w_i$, and $t_*^{\mathbf{h_{-i}}}$ is the total number of occupied tables. -Of particular note for our discussion is that in order to calculate these conditional distributions we must know the table assignments $\mathbf{z}_{-i}$ for each of the words in $\mathbf{w}_{-i}$. Moreover, in the Gibbs samplers often used for inference in these kinds of models, the counts are constantly changing over multiple samples, with tables going in and out of existence frequently. This can create significant bookkeeping issues in implementation, and motivated GGJ06 to present a method of computing approximate table counts based on word frequencies only. - -\section{Approximating Table Counts} -\begin{figure}[t] -\begin{center} -\includegraphics[scale=0.5]{approximations.pdf} -\end{center} -\caption[]{Comparison of several methods of approximating the number of tables occupied by words of different frequencies. -For each method, results using $\alpha = \{100, 1000, 10000, 100000\}$ are shown (from bottom to top). -Solid lines show the expected number of tables, computed using (\ref{eqn:true_expected}) and assuming $P_1$ is a fixed uniform distribution over a finite vocabulary (values computed using the Digamma formulation (\ref{eqn:digamma}) are the same). -Dashed lines show the values given by the Antoniak approximation (\ref{eqn:antoniak_approximation}) (the line for $\alpha = 100$ falls below the bottom of the graph). -Stars show the mean of empirical table counts as computed over 1000 samples from an MCMC sampler in which $P_1$ is a fixed uniform distribution, as in the unigram LM. -Circles show the mean of empirical table counts when $P_1$ is inferred, as in the bigram LM. Standard errors in both cases are no larger than the marker size. -All plots are based on the 30114-word vocabulary and frequencies found in sections 0-20 of the WSJ corpus.} -\label{fig:graphs} -\end{figure} - -Rather than explicitly tracking the number of tables $t_w$ associated with each word $w$ in their bigram model, GGJ06 approximate the table counts using the expectation $E[t_{w}]$. Expected counts are used in place of $t_{w_i}^{\mathbf{h_{-i}}}$ and $t_*^{\mathbf{h_{-i}}}$ in~(\ref{eq:hdp_p1}). The exact expectation, due to \newcite{antoniak74}, is -\begin{align} -E[t_w] = \alpha_1 P_1(w) \sum_{i=1}^{n_w} \frac{1}{\alpha_1 P_1(w) + i - 1} -\label{eqn:true_expected} -\end{align} -Antoniak also gives an approximation to this expectation: -\begin{align} -E[t_w] \approx \alpha_1 P_1(w) \log \frac{n_w + \alpha_1 P_1(w)}{\alpha_1 P_1(w)} -\label{eqn:antoniak_approximation} -\end{align} -but provides no derivation. Due to a misinterpretation of \newcite{antoniak74}, GGJ06 use an approximation that leaves out all the $P_1(w)$ terms from (\ref{eqn:antoniak_approximation}).\footnote{The authors of GGJ06 realized this error, and current implementations of their models no longer use these approximations, instead tracking table counts explicitly.} -Figure \ref{fig:graphs} compares the approximation to the exact expectation when the base distribution is fixed. The approximation is fairly good when $\alpha P_1(w) > 1$ (the scenario assumed by Antoniak); however, in most NLP applications, $\alpha P_1(w) < 1$ in order to effect a sparse prior. (We return to the case of non-fixed based distributions in a moment.) -As an extreme case of the paucity of this approximation consider $\alpha_1 P_1(w) = 1$ and $n_w=1$ (i.e. only one customer has entered the restaurant): clearly $E[t_w]$ should equal $1$, but the approximation gives $log(2)$. - - -We now provide a derivation for (\ref{eqn:antoniak_approximation}), which will allow us to obtain an $\mathcal{O}(1)$ formula for the expectation in (\ref{eqn:true_expected}). First, we rewrite the summation in (\ref{eqn:true_expected}) as a difference of fractional harmonic numbers:\footnote{Fractional harmonic numbers between 0 and 1 are given by $ H_F =\int_0^1 \frac{1 -x^F} {1 -x} dx$. All harmonic numbers follow the recurrence $H_F = H_{F-1} + \frac{1}{F}$.} -\begin{align} -\label{eqn:harmonic} -%\!\!\!\! E[t_w] = \alpha_1 P_1(w) \Big [ H_{(\alpha_1 P_1(w)+n_w-1)} - H_{(\alpha_1 P_1(w)-1)} \Big ] - H_{(\alpha_1 P_1(w)+n_w-1)} - H_{(\alpha_1 P_1(w)-1)} -\end{align} -Using the recurrence for harmonic numbers: -%\end{equation*} -\begin{multline} -\!\!\!\!\!\! E[t_w] \approx \alpha_1 P_1(w) \Big[ H_{(\alpha_1 P_1(w)+n_w)} - \frac{1}{\alpha_1 P_1(w)+n_w}\\ - H_{(\alpha_1 P_1(w) + n_w)} + \frac{1}{\alpha_1 P_1(w)} \Big ] -\end{multline} -We then use the asymptotic expansion, \mbox{$H_F \approx \log{F} + \gamma + \frac{1}{2F}$}, omiting trailing terms which are $\mathcal{O}(F^{-2})$ and smaller powers of $F$:\footnote{Here, $\gamma$ is the Euler-Mascheroni constant.} -\begin{equation*} -\mathsmaller{E[t_w] \approx \alpha_1 P_1(w) \log \frac{n_w + \alpha_1 P_1(w)}{\alpha_1 P_1(w)} + \frac{n_w}{2(\alpha_1 P_1(w)+n_w)}} -%\label{eqn:harm_approx} -\end{equation*} - -Omitting the trailing term leads to the approximation in \newcite{antoniak74}. -However, we can obtain an exact formula for the expectation by -utilising the relationship between the Digamma function and the harmonic numbers: \mbox{$\psi(n) = H_{n-1} - \gamma$}.\footnote{Accurate $\mathcal{O}(1)$ approximations of the Digamma function are readily available.} -Thus we can rewrite (\ref{eqn:harmonic}) as:\footnote{(\ref{eqn:digamma}) can be derived from (\ref{eqn:true_expected}) using: $\psi(x+1) - \psi(x) = \frac{1}{x}$.} -%\begin{equation} -\begin{multline} -%\mathsmaller{ -E[t_w] = \alpha_1 P_1(w) \cdot \\ - \big [\psi{(\alpha_1 P_1(w)+n_w)} - \psi{(\alpha_1 P_1(w)}) \big ] -\label{eqn:digamma} -%} -\end{multline} -%\end{equation} - -%The mean squared error of Eq.~\ref{eqn:antoniak_approximation} over the range $1\times10^{-4} < \alpha P_0(w) < 1$ in $1\times10^{-4}$ increments, and $n_w \in [1,20]$, is $1.38$. For Eq.~\ref{eqn:harmonic} with the extra expansion terms it's $0.14$, while with the Digamma function it's $6\times10^{-29}$. -%Figure \ref{fig:graphs} compares empirically observed table counts with their exact and approximate expectations, clearly showing the poor quality of the GGJ06 approximation. - -A significant caveat here is that the expected table counts given by (\ref{eqn:true_expected}) and (\ref{eqn:digamma}) are only valid when the base distribution is a constant. However, in hierarchical models such as GGJ06's bigram model and HDP models, the base distribution is not constant and instead must be inferred. As can be seen in Figure~\ref{fig:graphs}, table counts can diverge considerably from the expectations based on fixed $P_1$ when $P_1$ is in fact not fixed. Thus, (\ref{eqn:digamma}) can be viewed as an approximation in this case, but not necessarily an accurate one. Since knowing the table counts is only necessary for inference in hierarchical models, but the table counts cannot be approximated well by any of the formulas presented here, we must conclude that the best inference method is still to keep track of the actual table counts. The naive method of doing so is to store which table each customer in the restaurant is seated at, incrementing and decrementing these counts as needed during the sampling process. In the following section, we describe an alternative method that reduces the amount of memory necessary for implementing HDPs. This method is also appropriate for hierarchical Pitman-Yor processes, for which no closed-form approximations to the table counts have been proposed. - - -\section{Efficient Implementation of HDPs} - -As we do not have an efficient expected table count approximation for hierarchical models we could fall back to explicitly tracking which table each customer that enters the restaurant sits at. -However, here we describe a more compact representation for the state of the restaurant that doesn't require explicit table tracking.\footnote{\newcite{teh06hdp} also note that the exact table assignments for customers are not required for prediction.} -Instead we maintain a histogram for each dish $w_i$ of the frequency of a table having a particular number of customers. -Figure \ref{fig:histogram} depicts the histogram and explicit representations for the CRP state in Figure \ref{fig:tables}. - -\begin{figure} -%\begin{center} -%\includegraphics[width=0.8\columnwidth]{tables_histogram.pdf} -%\end{center} -\begin{tabular}{l} -{\bf Explicit table tracking:} \\ -customer($w_i$) $\rightarrow$ table($z_i$) \\ -{\small $\Big \{a:1,\ b:1,\ c:2,\ d:2,\ e:3,\ f:4,\ g:5,\ h:5 \Big \}$} \\ -table($z_i$) $\rightarrow$ label($\ell$) \\ -{\small $\Big \{1: The,\ 2: cats,\ 3: cats,\ 4: meow,\ 5: cats \Big \} $} -\vspace{0.05cm} \\ -\bf{Histogram:} \\ -word type $\rightarrow \Big \{$ table occupancy $\rightarrow$ frequency $\Big \}$ \\ -{\small $\Big \{\ The : \{2:1\},\ cats : \{1:1,\ 2:2\},\ meow : \{1:1\} \Big \}$} \\ -\end{tabular} - -\caption[]{The explicit table tracking and histogram representations for Figure \ref{fig:tables}.} -\label{fig:histogram} -\end{figure} - -Our alternative method of inference for hierarchical Bayesian models takes advantage of their exchangeability, which makes it unnecessary to know exactly which table each customer is seated at. The only important information is how many tables exist with different numbers of customers, and what their labels are. We simply maintain a histogram for each word type $w$, which stores, for each number of customers $m$, the number of tables labeled with $w$ that have $m$ customers. -Figure \ref{fig:histogram} depicts the explicit representation and histogram for the CRP state in Figure \ref{fig:tables}. - -Algorithms \ref{alg:increment} and \ref{alg:decrement} describe the two operations required to maintain the state of a CRP.\footnote{A C++ template class that implements the algorithm presented is made available at: {http://homepages.inf.ed.ac.uk/tcohn/}} -When a customer enters the restaurant (Alogrithm \ref{alg:increment})), we sample whether or not to open a new table. If not, we sample an old table proportional to the counts of how many customers are seated there and update the histogram. When a customer leaves the restaurant (Algorithm \ref{alg:decrement}), we decrement one of the tables at random according to the number of customers seated there. By exchangeability, it doesn't actually matter which table the customer was ``really" sitting at. - -\begin{algorithm}[t] -\caption{A new customer enters the restaurant} -\begin{small} -\begin{algorithmic}[1] -\State $w$: word type -\State $P_0^w$: Base probability for $w$ -\State $\mbox{HD}_w$: Seating Histogram for $w$ -\Procedure{\footnotesize INCREMENT}{$w, P_0^{w}, \mbox{HD}_w$} - - \State $p_{share} \gets \frac{n_{w}^{\mathbf{w}_{-1}}}{n_{w}^{\mathbf{w}_{-1}} + \alpha_0}$ \Comment{share an existing table} - \State $p_{new} \gets \frac{\alpha_0 \times P_0^{w}}{n_{w}^{\mathbf{w}_{-1}} + \alpha_0}$ \Comment{open a new table} - - \State $r \gets random(0, p_{share} + p_{new})$ - \If{$r < p_{new}\ \mbox{or}\ n_{w}^{\mathbf{w}_{-1}} = 0$} - \State $\mbox{HD}_w[1] = \mbox{HD}_w[1] + 1$ - \Else - \Statex \Comment{Sample from the histogram of customers at tables} - \State $r \gets random(0, n_{w}^{\mathbf{w}_{-1}})$ - \For{$c \in \mbox{HD}_w$} \Comment{$c$: customer count} - \State $r = r - (c \times \mbox{HD}_w[c])$ - \If{$r \leq 0$} - \State $\mbox{HD}_w[c] = \mbox{HD}_w[c] + 1$ - \State Break - \EndIf - \EndFor - \EndIf - \State $n_{w}^{\mathbf{w}} = n_{w}^{\mathbf{w}_{-1}} + 1$ \Comment{Update token count} -\EndProcedure -\end{algorithmic} -\end{small} -\label{alg:increment} -\end{algorithm} - -\begin{algorithm}[t] -\caption{A customer leaves the restaurant} -\begin{small} -\begin{algorithmic}[1] -\State $w$: word type -\State $\mbox{HD}_w$: Seating histogram for $w$ -\Procedure{\footnotesize DECREMENT}{$w, P_0^{w}, \mbox{HD}_w$} - \State $r \gets random(0, n_{w}^{\mathbf{w}})$ - \For{$c \in \mbox{HD}_w$} \Comment{$c$: customer count} - \State $r = r - (c \times \mbox{HD}_w[c])$ - \If{$r \leq 0$} - \State $\mbox{HD}_w[c] = \mbox{HD}_w[c] - 1$ - \If{$c > 1$} - \State $\mbox{HD}_w[c - 1] = \mbox{HD}_w[c - 1] + 1$ - \EndIf - \State Break - \EndIf - \EndFor - \State $n_{w}^{\mathbf{w}} = n_{w}^{\mathbf{w}} - 1$ \Comment{Update token count} -\EndProcedure -\end{algorithmic} -\end{small} -\label{alg:decrement} -\end{algorithm} - -%\vspace{-0.05in} -\section{Conclusion} -We've shown that the \mbox{HD}P approximation presented in GGJ06 contained errors and inappropriate assumptions such that it significantly diverges from the true expectations for the most common scenarios encountered in NLP. -As such we emphasise that that formulation should not be used. -Although (\ref{eqn:digamma}) allows $E[t_w]$ to be calculated exactly for constant base distributions, for hierarchical models this is not valid and no accurate calculation of the expectations has been proposed. -As a remedy we've presented an algorithm that efficiently implements the true \mbox{HD}P without the need for explicitly tracking customer to table assignments, while remaining simple to implement. - - -\section*{Acknowledgements} -The authors would like to thank Tom Griffiths for providing the code used to produce Figure \ref{fig:graphs} and acknowledge the support of the EPSRC (Blunsom, grant EP/D074959/1; Cohn, grant GR/T04557/01). - - -\bibliographystyle{scrunchacl} -\newcommand{\bibsnip}{\vspace{-1ex}} -\begin{small} -\bibliography{standard} -\end{small} - -\end{document} diff --git a/report/pyp_clustering/acl09-short/histogram_1.R b/report/pyp_clustering/acl09-short/histogram_1.R deleted file mode 100644 index cfbea84b..00000000 --- a/report/pyp_clustering/acl09-short/histogram_1.R +++ /dev/null @@ -1,8 +0,0 @@ -type = matrix(c(1,0,0, 0,0,0, 0,0,0), nr=3) -dimnames(type)=list(Type=c("0", "1", "2"),Constituent=c("the","cats","meow")) - -pdf('histogram_1.pdf', paper="special", width=18, height=10, onefile=FALSE,pointsize=40) - -barplot(type, axes=FALSE, space=c(0.5,0.5,0.5,2.0,0.5,0.5,2.0,0.5,0.5), xpd=F,beside=TRUE, -legend=rownames(type), ylab="Tables", ylim=range(0,2), col=c("black","grey","darkblue"), las=1) -axis(side=2, at=c(0,1,2)) diff --git a/report/pyp_clustering/acl09-short/histogram_1.pdf b/report/pyp_clustering/acl09-short/histogram_1.pdf 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Note that the encoding and the font should match. If T1 -% does not look nice, try deleting the line with the fontenc. -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% -%% abbreviations - -%% for tables -\newcommand{\mc}{\multicolumn} -\newcommand{\lab}[1]{\multicolumn{1}{c}{#1}} -\newcommand{\ind}[1]{{\fboxsep1pt\raisebox{-.5ex}{\fbox{{\tiny #1}}}}} - -%% for dcolumn -%\newcolumntype{d}{D{.}{.}{1.4}} -%\newcolumntype{s}{D{.}{.}{0.3}} - -%% markup -%\renewcommand{\key}[1]{\alert{\textit{#1}}} -\newcommand{\buffer}[1]{{\color{blue}\textbf{#1}}} -\newcommand{\pred}[1]{\code{#1}} - -%% colors -\newcommand{\textred}[1]{\alert{#1}} -\newcommand{\textblue}[1]{\buffer{#1}} -\definecolor{tablecolor}{cmyk}{0,0.3,0.3,0} -\newcommand{\keytab}[1]{\mc{1}{>{\columncolor{tablecolor}}d}{#1}} - -% rules -\newcommand{\psr}[2]{#1 $\rightarrow \langle $ #2 $\rangle$} - -\newenvironment{unpacked_itemize}{ -\begin{itemize} - \setlength{\itemsep}{10pt} - \setlength{\parskip}{0pt} - \setlength{\parsep}{0pt} -}{\end{itemize}} - -\newcommand{\condon}{\hspace{0pt} | \hspace{1pt}} -\definecolor{darkblue}{rgb}{0,0,0.6} -\newcommand{\blueexample}[1]{\textcolor{darkblue}{\rm #1}} - -%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% - -\newcommand{\bx}{\mathbf{x}} -\newcommand{\bz}{\mathbf{z}} -\newcommand{\bd}{\mathbf{d}} -\newcommand{\by}{\mathbf{y}} -\newcommand\bleu{${B{\scriptstyle LEU}}$} - - -\title[A Note on the Implemention of HDPs]{A Note on the Implementation of Hierarchical Dirichlet Processes} - -\author[Blunsom et al.]{{\bf Phil Blunsom}$^*$, Trevor Cohn$^*$, \\Sharon -Goldwater$^*$ and Mark Johnson$^\dagger$} - -\institute[Uni. of Edinburgh] % (optional, but mostly needed) -{ - $^*$School of Informatics, University of Edinburgh \\ - $^\dagger$Department of Cognitive and Linguistic Sciences, Brown University \\ -} - -\date{August 4, 2009} - - -\subject{Hierarchical Dirichlet Processes} - - -\pgfdeclareimage[height=1.0cm]{university-logo}{logo} -\logo{\pgfuseimage{university-logo}} - -\AtBeginSection[] -{ - \begin{frame}{Outline} - %\tableofcontents[currentsection,currentsubsection] - \tableofcontents[currentsection] - \end{frame} -} - - -%\beamerdefaultoverlayspecification{<+->} - - -\begin{document} - -\begin{frame} - \titlepage -\end{frame} - - -\begin{frame}[t]{Outline} -%\begin{exampleblock}{An example} -\vspace{0.5in} -\Large -\begin{unpacked_itemize} -\onslide<1-> \item GGJ06\footnote{S. Goldwater, T. Griffiths, M. Johnson. -Contextual dependencies in unsupervised word segmentation. ACL/COLING-06} -introduced an approximation for use in hierarchical Dirichlet process (HDP) inference: \\ -\onslide<2->{\alert{\textbf{It's wrong, don't use it.}}} -\onslide<3-> \item We correct that approximation for DP models. \\ -\onslide<4->{\alert{\textbf{However, this doesn't extend to HDPs.}}} -\onslide<5> \item But that's ok because we'll describe an efficient exact implementation. -\end{unpacked_itemize} -%\end{exampleblock} -\end{frame} - -\begin{frame} -\frametitle{The Chinese Restaurant Process} -In a Dirichlet Process unigram language model words $w_1 \ldots w_n$ are generated as follows: -\begin{align} -\nonumber G | & \alpha_0, P_0 &\sim & ~ \mbox{DP}(\alpha_0,P_0) \\ -\nonumber w_i | & G &\sim & ~ G -\end{align} -\begin{itemize} - \item $G$ is a distribution over an infinite set of words, - \item $P_0$ is the probability that an word will be in the support of $G$, - \item $\alpha_0$ determines the variance of $G$. -\end{itemize} -\vspace{0.2in} -One way of understanding the predictions made by the DP model is through the Chinese restaurant process (CRP) \dots -\end{frame} - -\begin{frame} -\frametitle{The Chinese Restaurant Process} -\only<1-9>{\vspace{-0.4in}} -\begin{figure} -\begin{center} - \only<1>{\includegraphics[scale=0.7]{tables0.pdf}} - \only<2>{\includegraphics[scale=0.7]{tables1.pdf}} - \only<3>{\includegraphics[scale=0.7]{tables2.pdf}} - \only<4>{\includegraphics[scale=0.7]{tables3.pdf}} - \only<5>{\includegraphics[scale=0.7]{tables4.pdf}} - \only<6>{\includegraphics[scale=0.7]{tables5.pdf}} - \only<7>{\includegraphics[scale=0.7]{tables7.pdf}} - \only<8>{\includegraphics[scale=0.7]{tables8.pdf}} - \only<9>{\includegraphics[scale=0.7]{tables6.pdf}} -\end{center} -\end{figure} -\only<1-6>{ -\vspace{-0.6in} -Customers (words) enter a restaurant and choose a table according to the distribution: -\begin{align} -\nonumber P(z_i = k | w_i = w, \mathbf{z}_{-i}) = \left\{ -\begin{array}{ll} - \frac{n_k^{\mathbf{z}_{-i}}}{n_w + \alpha_0 P_0(w)}, 0 \leq k < |k| \\ - \\ \frac{\alpha_0 P_0(w)}{n_w + \alpha_0 P_0(w)}, k = |k| -\end{array} \right. -\end{align} -%where $\mathbf{z}_{-i} = z_1 \dots z_{i-1}$ are the table assignments of the previous customers, $n_k^{\mathbf{z}_{-i}}$ is the number of customers at table $k$ in ${\mathbf{z}_{-i}}$, and $K(\mathbf{z}_{-i})$ is the total number of occupied tables. -} -\only<7-9>{ -\vspace{-0.4in} -The 7$^{th}$ customer `{\em the}' enters the restaurant and choses a table from -those already seating `{\em the}', or opening a new table: -} -\only<7>{ -\begin{align} -\nonumber P(z_6 = 0 | w_6 = the, \mathbf{z}_{-6}) = \frac{2}{3 + \alpha_0 P_0(the)} -\end{align} -} -\only<8>{ -\begin{align} -\nonumber P(z_6 = 2 | w_6 = the, \mathbf{z}_{-6}) = \frac{1}{3 + \alpha_0 P_0(the)} -\end{align} -} -\only<9>{ -\begin{align} -\nonumber P(z_6 = 4 | w_6 = the, \mathbf{z}_{-6}) = \frac{P_0(the)}{3 + \alpha_0 P_0(the)} -\end{align} -} -\only<7-9>{\vspace{0.32in}} -\end{frame} - -\begin{frame} -\frametitle{Approximating the table counts} -\begin{figure} -\begin{center} - \includegraphics[scale=0.7]{tables_expectation.pdf} -\end{center} -\end{figure} - -\begin{itemize} - \item GGJ06 sought to avoid explicitly tracking tables by reasoning under -the expected table counts ($E[t_w]$). - -\item Antoniak(1974) derives the expected table count as equal to the recurrence: -\begin{align} -\nonumber E[t_w] = \alpha_0 P_0(w) \sum_{i=1}^{n_w} \frac{1}{\alpha_0 P_0(w) + i - 1} -\label{eqn:true_expected} -\end{align} -\item Antoniak also suggests an approximation to this expectation which GGJ06 - presents as: \only<2>{\alert{(corrected)}} -\only<1> { -\begin{align} - \nonumber E[t_w] \approx \alpha_0 \log \frac{n_w + \alpha_0}{\alpha_0} -\end{align} -} -\only<2> { -\begin{align} - \nonumber E[t_w] \approx \alpha_0 \alert{P_0(w)} \log \frac{n_w + \alpha_0 - \alert{P_0(w)}}{\alpha_0 \alert{P_0(w)}} -\end{align} -\vspace{-0.32cm} -} -\end{itemize} -\end{frame} - - -\begin{frame} -\frametitle{A better table count approximation} -\begin{itemize} -\item Antoniak's approximation makes two assumptions: - \begin{unpacked_itemize} - \item $\alpha_0$ is large, not the predominant situation in recent applications which employ a DP as a sparse prior, - \item $P_0(w)$ is constant, which is not applicable to HDPs. - \end{unpacked_itemize} -\vspace{1.0cm} -\item In our paper we derive an improved approximation based on a difference of digamma ($\psi$) functions: -\begin{align} -\nonumber E[t_w] = \alpha_0 P_0(w) \cdot \Bigg [\psi{\Big (\alpha_0 -P_0(w)+n_w \Big)} - \psi{\Big (\alpha_0 P_0(w)} \Big ) \Bigg ] -\end{align} -\vspace{0.5cm} -\item However the restriction on $P_0(w)$ being constant remains \dots -\end{itemize} -\end{frame} - -\begin{frame} -\frametitle{DP performance} -\begin{figure} -{\centering \includegraphics[scale=0.45]{code/plot0.pdf}} -\end{figure} -\end{frame} - -\begin{frame} -\frametitle{DP performance} -\begin{figure} -{\centering \includegraphics[scale=0.45]{code/plot1.pdf}} -\end{figure} -\end{frame} - -\begin{frame} -\frametitle{DP performance} -\begin{figure} -{\centering \includegraphics[scale=0.45]{code/plot2.pdf}} -\end{figure} -\end{frame} - -\begin{frame} -\frametitle{HDP performance} -\begin{figure} -{\centering \includegraphics[scale=0.45]{code/plot3.pdf}} -\end{figure} -\end{frame} - -\begin{frame} -\frametitle{Histogram Method} -\begin{unpacked_itemize} - \item At this point we don't have a useful approximation of the expected table - counts in a HDP model. - \item However, we can describe a more compact representation for the state of the restaurant that doesn't require explicit table tracking. - \item Instead we maintain a histogram for each dish $w_i$ of the frequency of a table having a particular number of customers. -\end{unpacked_itemize} -\end{frame} - -\begin{frame}[t] -\frametitle{Histogram Method} -\begin{center} - \only<1>{\includegraphics[scale=0.7]{tables0.pdf}} - \only<2>{\includegraphics[scale=0.7]{tables1.pdf}} - \only<3>{\includegraphics[scale=0.7]{tables2.pdf}} - \only<4>{\includegraphics[scale=0.7]{tables3.pdf}} - \only<5>{\includegraphics[scale=0.7]{tables4.pdf}} - \only<6>{\includegraphics[scale=0.7]{tables5.pdf}} - \only<7>{\includegraphics[scale=0.7]{tables7.pdf}} - \only<8>{\includegraphics[scale=0.7]{tables9.pdf}} -\end{center} -\vspace{-2.5cm} -\only<6->{\vspace{0.47cm}} -\begin{center} - \only<1>{\includegraphics[scale=0.2]{histogram_1.pdf}\hspace{-0.6cm}} - \only<2>{\includegraphics[scale=0.2]{histogram_2.pdf}\hspace{-0.5cm}} - \only<3>{\includegraphics[scale=0.2]{histogram_3.pdf}\hspace{-0.4cm}} - \only<4>{\includegraphics[scale=0.2]{histogram_4.pdf}\hspace{-0.3cm}} - \only<5>{\includegraphics[scale=0.2]{histogram_5.pdf}\hspace{-0.2cm}} - \only<6>{\includegraphics[scale=0.2]{histogram_6.pdf}} - \only<7>{\includegraphics[scale=0.2]{histogram_7.pdf}} - \only<8>{\includegraphics[scale=0.2]{histogram_8.pdf}} -\end{center} -\end{frame} - -\begin{frame} -\frametitle{Summary} -\begin{center} - \Large \textbf{The table count approximation of Goldwater et al. 2006 - is broken, \alert{don't use it!}} -\end{center} -\end{frame} - -\begin{frame} -% \frametitle{Summary} - \begin{center} - \Large Thank you. - \end{center} - -\begin{block}{References} - \footnotesize - \vspace{0.5cm} - P. Blunsom, T. Cohn, S. Goldwater and M. Johnson. A note on the - implementation of hierarchical Dirichlet processes, - {\em In the Proceedings of ACL-IJCNLP 2009}. \\ - \vspace{0.5cm} - C. E. Antoniak. 1974. Mixtures of dirichlet processes with - applications to bayesian nonparametric problems. - {\em The Annals of Statistics}, 2(6):1152-1174. \\ - \vspace{0.5cm} - S. Goldwater, T. Griffiths, M. Johnson. - Contextual dependencies in unsupervised word segmentation. - {\em In the Proceedings of (COLING/ACL-2006)}. - \vspace{0.5cm} -\end{block} -\end{frame} - -\end{document} diff --git a/report/pyp_clustering/acl09-short/slides.toc b/report/pyp_clustering/acl09-short/slides.toc deleted file mode 100644 index 8c353fcd..00000000 --- a/report/pyp_clustering/acl09-short/slides.toc +++ /dev/null @@ -1,2 +0,0 @@ -\beamer@endinputifotherversion {3.07pt} -\select@language {english} diff --git a/report/pyp_clustering/acl09-short/standard.bib b/report/pyp_clustering/acl09-short/standard.bib deleted file mode 120000 index 32984351..00000000 --- a/report/pyp_clustering/acl09-short/standard.bib +++ /dev/null @@ -1 +0,0 @@ -common/standard.bib \ No newline at end of file diff --git a/report/pyp_clustering/acl09-short/tables.graffle b/report/pyp_clustering/acl09-short/tables.graffle deleted file mode 100644 index ad34226a..00000000 --- a/report/pyp_clustering/acl09-short/tables.graffle +++ 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--git a/report/pyp_clustering/eval/.RData b/report/pyp_clustering/eval/.RData deleted file mode 100644 index a2403de6..00000000 Binary files a/report/pyp_clustering/eval/.RData and /dev/null differ diff --git a/report/pyp_clustering/eval/.Rhistory b/report/pyp_clustering/eval/.Rhistory deleted file mode 100644 index 316d69ea..00000000 --- a/report/pyp_clustering/eval/.Rhistory +++ /dev/null @@ -1,6 +0,0 @@ -data <- read.table("urdu.dat", header=TRUE) -data <- read.table("urdu.dat", header=TRUE) -data -data[1] -data[2] -plot(data[1],data[2]) diff --git a/report/pyp_clustering/eval/rand-25.png b/report/pyp_clustering/eval/rand-25.png deleted file mode 100644 index 8340913d..00000000 Binary files a/report/pyp_clustering/eval/rand-25.png and /dev/null differ diff --git a/report/pyp_clustering/eval/src-class.png b/report/pyp_clustering/eval/src-class.png deleted file mode 100644 index 89d50120..00000000 Binary files a/report/pyp_clustering/eval/src-class.png and /dev/null differ diff --git a/report/pyp_clustering/eval/src-word.png b/report/pyp_clustering/eval/src-word.png deleted file mode 100644 index 6925fff5..00000000 Binary files a/report/pyp_clustering/eval/src-word.png and /dev/null differ diff --git a/report/pyp_clustering/eval/trg-class.png b/report/pyp_clustering/eval/trg-class.png deleted file mode 100644 index ad2e738e..00000000 Binary files a/report/pyp_clustering/eval/trg-class.png and /dev/null differ diff --git a/report/pyp_clustering/eval/trg-pos.png b/report/pyp_clustering/eval/trg-pos.png deleted file mode 100644 index 4b7e2eef..00000000 Binary files a/report/pyp_clustering/eval/trg-pos.png and /dev/null differ diff --git a/report/pyp_clustering/eval/trg-word.len2.png b/report/pyp_clustering/eval/trg-word.len2.png deleted file mode 100644 index 1e97f34d..00000000 Binary files a/report/pyp_clustering/eval/trg-word.len2.png and /dev/null differ diff --git a/report/pyp_clustering/eval/trg-word.png b/report/pyp_clustering/eval/trg-word.png deleted file mode 100644 index 032eb4fd..00000000 Binary files a/report/pyp_clustering/eval/trg-word.png and /dev/null differ diff --git a/report/pyp_clustering/eval/urdu.R b/report/pyp_clustering/eval/urdu.R deleted file mode 100644 index 8c6fb1b7..00000000 --- a/report/pyp_clustering/eval/urdu.R +++ /dev/null @@ -1,5 +0,0 @@ -data <- read.table("urdu.dat", header=TRUE) -attach(data) -data.lm <- glm(BLEU ~ ConditionalEntropy) -plot(data$ConditionalEntropy,data$BLEU) -abline(data.lm) diff --git a/report/pyp_clustering/eval/urdu.dat b/report/pyp_clustering/eval/urdu.dat deleted file mode 100644 index 0f47774f..00000000 --- a/report/pyp_clustering/eval/urdu.dat +++ /dev/null @@ -1,10 +0,0 @@ -ConditionalEntropy BLEU -4.45 19.7 -4.49 20.9 -0 24.6 -3.25 21.7 -2.86 22.0 -3.03 20.4 -2.29 21.8 -1.85 22.2 -2.27 22.3 diff --git a/report/pyp_clustering/eval/urdu.txt b/report/pyp_clustering/eval/urdu.txt deleted file mode 100644 index 61badbc3..00000000 --- a/report/pyp_clustering/eval/urdu.txt +++ /dev/null @@ -1,34 +0,0 @@ - RAND: H(P|G) 4.61390472601 H(G|P) 4.46318493091 VI 9.07708965693 -19.7 - - - HIERO: H(P|G) 0.0 H(G|P) 4.49202511251 VI 4.49202511251 -20.9 - - - SAMT: 0 -24.6 - - -SRC-WORD: H(P|G) 3.14341282625 H(G|P) 3.24806419314 VI 6.39147701938 -21.7 - - -TRG-WORD: H(P|G) 2.49873406298 H(G|P) 2.8630796488 VI 5.36181371178 -22.0 - - -SRC-CLASS: H(P|G) 2.9544101134 H(G|P) 3.03429783958 VI 5.98870795298 -20.4 - - -TRG-CLASS: H(P|G) 2.09317817062 H(G|P) 2.28900201963 VI 4.38218019024 -21.8 - -TRG-CLASS-LEX-PHRASE: H(P|G) 2.08306186813 H(G|P) 2.27376071357 VI 4.3568225817 -22.3 - - TRG-POS: H(P|G) 1.68546811 H(G|P) 1.84741730383 VI 3.53288541383 -22.2 - - diff --git a/report/pyp_clustering/format-grammar-latex.pl b/report/pyp_clustering/format-grammar-latex.pl deleted file mode 100755 index e1fe3e45..00000000 --- a/report/pyp_clustering/format-grammar-latex.pl +++ /dev/null @@ -1,21 +0,0 @@ -#!/usr/bin/perl -w -use strict; -my $x = ''; -while(<>){ - if (/^$/) { print "\\hline\n"; next; } - if (/^(\d+)$/) { - $x=$1; - $x=~s/^(\d\d\d)(\d\d\d)(\d\d\d)$/$1,$2,$3/; - $x=~s/^(\d\d)(\d\d\d)(\d\d\d)$/$1,$2,$3/; - $x=~s/^(\d)(\d\d\d)(\d\d\d)$/$1,$2,$3/; - $x=~s/^(\d\d\d)(\d\d\d)$/$1,$2/; - $x=~s/^(\d\d)(\d\d\d)$/$1,$2/; - $x=~s/^(\d)(\d\d\d)$/$1,$2/; - next; - } - s/ \|\|\| LHSProb.*$//; s/ \|\|\| / \\rightarrow \\langle \\textrm{/; s/\[X(\d+)\]/\\textrm{X}^{$1}/; - s/ \|\|\| /},\\textrm{{\\emph /; - chomp; - print "$x & \$ $_}} \\rangle \$ \\\\\n"; - $x=""; -} diff --git a/report/pyp_clustering/llh.R b/report/pyp_clustering/llh.R deleted file mode 100644 index 907fc647..00000000 --- a/report/pyp_clustering/llh.R +++ /dev/null @@ -1,6 +0,0 @@ -data <- read.table("/Users/redpony/ws10smt/report/pyp_clustering/llh.dat", sep=" ", header=TRUE) -attach(data) -pdf("llh.pdf") -plot(Samples,C25,type="o",pch=23,col="blue",ylab="LLH") -lines(Samples,C10,type="o",col="red") -dev.off() diff --git a/report/pyp_clustering/llh.dat b/report/pyp_clustering/llh.dat deleted file mode 100644 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--git a/report/report.tex b/report/report.tex deleted file mode 100755 index af78104f..00000000 --- a/report/report.tex +++ /dev/null @@ -1,127 +0,0 @@ -%!TEX TS-program = pdflatex -%!TEX encoding = UTF-8 Unicode - -\documentclass[11pt]{report} -\usepackage{graphicx} -\usepackage{index} -\usepackage{varioref} -\usepackage{amsmath} -\usepackage{multirow} -\usepackage{theorem} % for examples -\usepackage{alltt} -\usepackage{ulem} -\usepackage{epic,eepic} -\usepackage{boxedminipage} -\usepackage{fancybox} -\usepackage{colortbl} -\usepackage[square]{natbib} -\usepackage{epsfig} -%\usepackage{subfig} -\usepackage{subfigure} -\usepackage{booktabs} -\usepackage{tikz} -\usepackage{algorithmic} -\usepackage{algorithm} - -%\usepackage[encapsulated]{CJK} -%\usepackage{ucs} -\usepackage[utf8x]{inputenc} -% use one of bsmi(trad Chinese), gbsn(simp Chinese), min(Japanese), mj(Korean); see: -% /usr/share/texmf-dist/tex/latex/cjk/texinput/UTF8/*.fd -%\newcommand{\cntext}[1]{\begin{CJK}{UTF8}{gbsn}#1\end{CJK}} -\newcommand{\cntext}[1]{} - -\oddsidemargin 0mm -\evensidemargin 5mm -\topmargin -20mm -\textheight 240mm -\textwidth 160mm - - - -\newcommand{\bold}{\it} -\renewcommand{\emph}{\it} - -\makeindex -\theoremstyle{plain} - -\newcommand{\nt}[2]{\textrm{#1}_{\framebox[5pt]{\scriptsize #2}}} -\newcommand{\ind}[1]{{\fboxsep1pt\raisebox{-.5ex}{\fbox{{\tiny #1}}}}} - -\begin{document} -\title{\vspace{-15mm}\LARGE {\bf Final Report}\\[2mm] -of the\\[2mm] -2010 Language Engineering Workshop\\[15mm] -{\huge \bf Models for\\ -Synchronous Grammar Induction\\[2mm] -{\tt \Large http://www.clsp.jhu.edu/workshops/ws10/groups/msgismt/}\\[15mm] -Johns Hopkins University\\[2mm] -Center for Speech and Language Processing}} -\author{\large Phil Blunsom, -Chris Callison-Burch, -Trevor Cohn, -Chris Dyer, -Jonathan Graehl, -Adam Lopez,\\ -\large -Jan Botha, -Vladimir Eidelman, -ThuyLinh Nguyen, -Ziyuan Wang, -Jonathan Weese, -\\ -\large Olivia Buzek, Desai Chen} -\normalsize - -\maketitle - -\section*{Abstract} -The last decade of research in Statistical Machine Translation (SMT) has seen rapid progress. The most successful methods have been based on synchronous context free grammars (SCFGs), which encode translational equivalences and license reordering between tokens in the source and target languages. Yet, while closely related language pairs can be translated with a high degree of precision now, the result for distant pairs is far from acceptable. In theory, however, the ``right'' SCFG is capable of handling most, if not all, structurally divergent language pairs. The 2010 Language Engineering Workshop {\emph Models of Synchronous Grammar Induction for SMT} had the goal to focus on the crucial practical aspects of acquiring such SCFGs from bilingual text. We started with existing algorithms for inducing unlabeled SCFGs (e.g. the popular Hiero model) and then used state-of-the-art unsupervised learning methods to refine the syntactic constituents used in the translation rules of the grammar. - -\phantom{.} - - -\newpage -\section*{Acknowledgments} -The participants at the workshop would like to thank everybody at Johns Hopkins University who made the summer workshop such a memorable --- and in our view very successful --- event. The JHU Summer Workshop is a great venue to bring together researchers from various backgrounds and focus their minds on a problem, leading to intense collaboration that would not have been possible otherwise. - -We especially would like to thank Fred Jelinek for heading the Summer School effort and Desir\'ee Cleves for her superhuman ability to keep things running smoothly. - -\phantom{.} - -\newpage -\section*{Team Members} - -\begin{itemize} -\item Phil Blunsom, Team Leader, University of Oxford -\item Chris Callison-Burch, Senior Researcher, Johns Hopkins University -\item Trevor Cohn, Senior Researcher, University of Sheffield -\item Chris Dyer, Senior Researcher, Carnegie Mellon University -\item Adam Lopez, Senior Researcher, University of Edinburgh -\item Jonathan Graehl, Senior Researcher, Information Sciences Institute, USC -\item Jan Botha, Graduate Student, University of Oxford -\item Vladimir Eidelman, Graduate Student, University of Maryland -\item Thuylinh Nguyen, Graduate Student, Carnegie Mellon University -\item Jonathan Weese, Graduate Student, Johns Hopkins University -\item Ziyuan Wang, Graduate Student, Johns Hopkins University -\item Olivia Buzek, Undergraduate Student, University of Maryland -\item Desai Chen, Undergraduate Student, Carnegie Mellon University -\end{itemize} -\tableofcontents - - -\include{introduction} -\include{SCFGs} -\include{setup} -\include{np_clustering} -\include{morphology/morphology} -\include{pr-clustering/posterior} -\include{decoding} -\include{training} - -\bibliographystyle{apalike} -\bibliography{biblio} - -\printindex - -\end{document} diff --git a/report/setup.tex b/report/setup.tex deleted file mode 100644 index eb655a77..00000000 --- a/report/setup.tex +++ /dev/null @@ -1,130 +0,0 @@ -\chapter{Experimental Setup} -\label{chapter:setup} - -Our approach is based upon the popular and influential Hiero system \citep{chiang:2007} which uses a synchronous context free grammar (SCFG) to model translation. -This translation system uses only a single non-terminal symbol and therefore the system is inherently stateless. -However, we know that using a richer set of non-terminals can greatly improve translation, as evidenced by the improvments obtained by SAMT system \citep{samt} which augments a Hiero-style SCFG model with syntactic labels. -This is best explained in terms of the generalisation capability: a single category grammar can create all manner of string-pairs, the majority of which are nonsensical and agrammatical, while a model with syntactic categories inherently limits the sets of string pairs to those which are grammatical (largely). -This can be seen from the following example rules, showing how rules can be combined to arrive at ungrammatical string pairs. -\begin{align} -X &\rightarrow \langle \mbox{does not}~X, \mbox{ne}~X~\mbox{pas} \rangle \label{eq:nepas}\\ -X &\rightarrow \langle \mbox{cat}, \mbox{chat} \rangle \label{eq:chat} \\ -X &\Rightarrow^{\ref{eq:nepas},\ref{eq:chat}} \langle \mbox{does not cat}, \mbox{ne cat pas} \rangle -\nonumber -\end{align} -If the non-terminals in the above rules were replaced with, e.g., parts-of-speech, such that rule \ref{eq:nepas} required a verb instead of an X in its right hand side, and the rule \ref{eq:chat} rewrote a noun, then this ungrammatical string pair would no longer be licenced. - -As such, the single-category model licenses all manner of word-salad output, thus relying on the language model to salvage a coherent sentence from these options. -In contrast, the set of translation options for the grammar with syntactic labels is much smaller and more coherent, and thus the language model has less heavy lifting to do. -This setting plays well to the strengths of a n-gram language model which can accurately model local coherence but is unable to model global sentence-level effects (which are modelled by the syntactic translation model). -%In addition, a treebank parser and an n-gram language model have different strengths -- the parser can ensure more global grammatical coherence but over-generalises at the lexical level, while the n-gram model does the opposite. - -The central aim of the project was to induce automatically a rich translation grammar to realise some of the performance gains resulting from the use of linguistic grammars, but without using linguistic resources such as treebank parsers. -This allows our approach to be more easily ported to work for translating a variety of languages, rather than being constrained to just translating into languages with good syntactic resources (typically English). - -\section{Distributional Hypothesis} - -Underlying most models of grammar induction is the distributional hypothesis. This theory states that -``words that occur in the same contexts tend to have similar meaning'' \citep{harris:54}. Although phrased in terms of semantics, the distributional hypothesis applies equally to syntax, that is, words that can be substituted for one another most often share the same syntactic category (in general, semantics implies syntax). This is evidenced by the wide-spread use of the substitution test in theories of syntax to determine the constituency and syntactic category of a word or phrase. - -The majority of work on monolingual grammar induction has used some notion of context to inform the induced categories. This is best seen in the work of Alex Clark who uses the context surrounding a phrase to determine its category, and in Dan Klein's work, which uses context to determine constituency. In this project we follow the lead of these earlier works on monolingual grammar induction by using context to inform our clustering of words and phrases, such that words that appear in similar contexts are assigned to the same cluster. We expect that this clustering should bear a strong resemblance to the underlying syntax and, to some extent, the semantics of the language, and therefore improve translation accuracy. - -Our bilingual translation setting differs from the earlier monolingual settings in which most grammar induction research has been performed. We seek to label a broad range of n-grams (so-called phrases) as supplied from the phrase extraction process. These n-grams will be both constituents and non-constituents. The use of non-constituent translation units has been shown consistently to outperform systems which use only constituents in terms of translation quality. For this reason how grammar induction system must be able to infer useful syntactic categories for these non-constituent n-grams. - -\section{Clustering Configuration} - -It still remains to define what we mean by context. Well we could choose the entire sentence or even document in which the phrase appears, we adopt a more local definition of context. We use a window of one or two words preceding the phrase and one or two words following. This local context is still highly informative about the syntactic role of the phrase, but given its small size we expect to observe the same context many times in a small corpus. That is, the sparsity of the data should no lo - -It still remains to define what we mean by context. Well we could choose the entire sentence or even document in which the phrase appears, we adopt a more local definition of context. We use a window of one or two words preceding the phrase and one or two words following. This local context is still highly informative about the syntactic role of the phrase, but given its small size we expect to observe the same context many times in a small corpus. That is, the sparsity of the data should no longer be a serious problem, as it would be for full sentences or example. - -The input to the clustering system are bilingual phrases in their bilingual contexts, as extracted using the standard phrase-based grammar extraction pipeline. However we choose to primarily perform monolingual clustering by discarding one side of the data, typically the source. Focusing our attention on the target side of the corpus replicates the configuration which is known to work best for syntactic translation. The target-side syntax is more informative than source-side syntax, it better models the target language and also avoids an errorful projection step onto the target (due to the grammars of the two languages not being isomorphic). On the flip side, source side syntax could be more useful in pruning the beam search for decoding, where we can use the source parse to prune away improbable items before translating into the target language. We will determine experimentally whether the effects of better pruning versus better modelling target grammar are more important for translation. -nger be a serious problem, as it would be for full sentences or example. - -The input to the clustering system are bilingual phrases in their bilingual contexts, as extracted using the standard phrase-based grammar extraction pipeline. This is illustrated in Figure~\ref{fig:extraction}. Instead of using the bilingual data directly, we choose to primarily perform monolingual clustering by discarding one side of the data, typically the source. Focusing our attention on the target side of the corpus replicates the configuration which is known to work best for syntactic translation. The target-side syntax is more informative than source-side syntax, as it better models the target language, thus better informing reordering and lexical selection. Target-side syntax avoids an errorful projection step onto the target, due to the grammars of the two languages rarely being even approximately isomorphic. On the flip side, source side syntax could be more useful in pruning the beam search for decoding, where we can use the source parse to prune away improbable items before translating into the target language. We will determine experimentally whether the effects of better pruning versus better modelling target grammar are more important for translation. - -\begin{CJK}{UTF8}{gbsn} -\begin{figure} -% input: 今天 有 æ£’çƒ æ¯”èµ› å— ? ||| are there any baseball games today ? ||| 1-0 1-1 1-2 2-3 3-4 0-5 4-6 5-6 -% from btec/split.zh-en.al line 26 -\centering -\subfigure[Example word-aligned sentence pair]{\hfill \includegraphics{align} \hfill} - -\subfigure[Some bilingual phrases and contexts extracted from (a)]{ -\centering -\begin{tabular}{rcl} -\toprule -$<$s$>$ $<$s$>$ & are there any baseball games today & ? $<$/s$>$ \\ -$<$s$>$ $<$s$>$ & 今天 有 æ£’çƒ æ¯”èµ› & å— ? \\ -\midrule -baseball games & today & ? $<$/s$>$ \\ -$<$s$>$ $<$s$>$ & 今天 & 有 æ£’çƒ \\ -\midrule -$<$s$>$ $<$s$>$ & are there any & baseball games \\ -$<$s$>$ 今天 & 有 & æ£’çƒ æ¯”èµ› \\ -\midrule -any baseball & games & today ? \\ -有 æ£’çƒ & 比赛 & å— ? \\ -\bottomrule -\end{tabular}} -\caption{Example showing how a sentence pair gives rise to bilingual phrases and their contexts. These serve as input to the clusterer, typically by discarding the source side and processing the target.} -\label{fig:extraction} -\end{figure} -\end{CJK} - -In addition to the choice of source versus target language, we also consider the choice of lexical units. Our default option is to use words, but we also consider using automatically induced parts of speech in their stead. To do this we replace the words in the corpus with their corresponding word classes, and then run the extraction heuristics to obtain the phrase context graphs over parts-of-speech. This improves the density of the counts, because many different phrases and contexts will share the same part-of-speech sequence. In addition the part-of-speech induction algorithm uses a different mechanism for learning the labelling -- namely, a form of hidden Markov model with a hard-clustering constraint -- and therefore would be expected to present complementary information to our methods of indepedently clustering each instance based solely on its context. For these reason we expect that using word classes rather than words will improve the results of our clustering methods. There is one caveat: errors in the word-classes will artifically conflate many disparate syntactic categories. This is not a huge problem for the contexts, where it will resemble noise in the data, however for phrases this is more of a problem. All of our models make the assumption that phrases are assigned very few different cluster labels, but when using word class sequences for phrases this will no longer be valid. For this reason we have also experimented with a conglomerate representation where the contexts are represented as word-classes but the phrases are composed of words. This means that we obtain the expected improvements in data sparsity, but without also conflating phrases which are not syntactically or semantically identical. - -The set of phrases and contacts are aggregated over the corpus, and are then collated into a file consisting of phrases, context and their occurrence counts. We refer to this structure as the phrase -- context graph, as illustrated in Figure \ref{fig:bipartite}. This is a bipartite graph with nodes for each phrase type and context type, and edges for instances of a phrase occurring in a given context. The graph forms the input to the clustering algorithm, which labels the edges with cluster indices. In the example, we expect that the clustering will produce two different clusters for nouns (the sub-graph to the right of `deal') and for verbs (the sub-graph to the left). This clustering maximises internal connectivity within each sub-graph while minimising external connectivity between the two sub-graphs. In other words, outgoing edges from phrases and contexts are largely assigned the same cluster label. - -\begin{figure} -\includegraphics[width=\textwidth]{deal} -\caption{Example of a phrase-context graph, centered around `deal'. Phrases are shown as unshaded nodes and contexts are shaded in pink. Contexts include the left and right word surrounding the phrase, with an underscore denoting the gap for the phrase. Edges specify that phrase appears in a given context, and the edge weight denotes the occurence count.} -\label{fig:bipartite} -\end{figure} - -The notation used in the remainder of the paper for describing the clustering models and their inputs and outputs is given in Table~\ref{tab:notation}. - -\begin{table} -\begin{tabular}{cp{.7\textwidth}} -\toprule - symbol & meaning \\ -\midrule - $\mathbf{p} = (p_1, \ldots, p_n)$ & a phrase (n-gram) of word tokens \\ - $\mathbf{c} = (\ldots, c_{-2}, c_{-1}, c_1 c_2, \ldots)$ & a context of immediate words surrounding a phrase, with the index signifying the distance to the left (negative indices) or right (positive indices) of the phrase \\ - $e = (p, c)$ & a edge denoting a phrase, $p$, occuring in context $c$ \\ - $z$ & label assigned to an edge, denoting the cluster or non-terminal assigned to the phrase in context \\ - $K$ & number of clusters, $z \in \{1,2, \ldots, K\}$ \\ - $P$ & set of unique phrases \\ - $C$ & set of unique contexts \\ - $C_p$ & set of contexts in which $p$ has occurred \\ - $P_c$ & set of phrases occuring in context $c$ \\ -\bottomrule -\end{tabular} -\caption{Notation used throughout this paper.} -\label{tab:notation} -\end{table} - -\section{Pipeline} - -Brief overview of the pipeline, including phrase-extraction. - -\section{Data sets}\label{sec:datasets} - -\section{Evaluation} - -Given an induced clustering, we run the pipeline to completion to produce translations for our test set. We then compare these translations with human authored reference translations in order to evaluate the quality. We use the standard metric, blue, to measure the quality of the output translations. However as an alternative metric we consider an intrinsic evaluation of the clustering by comparing the induced labels against linguistic categories. That is, without running the decoder to create translations. This saves considerable time and also gives us an alternative view as to the quality of the clustering. We now describe each of these evaluation metrics in the following section. - -\subsubsection{BLEU} - - -\subsubsection{Conditional Entropy} - -The second evaluation metric measures the similarity between the induced cluster labels and the syntactic categories predicted by a treebank-trained parser. This metric is considerably cheaper to evaluate than BLEU as it does not require a decoding pass, but instead works directly on the clustering output. Our objective is to maximise the quality of translation, and we trust BLEU to do this more directly than this instrinsic metric. However, we expect there to be interesting information in this metric, and the potential to short-cut the evaluation thus improving the turn-around time for experimental evaluation. - -We measure the conditional entropy of the ``gold-standard'' categories for each phrase in context given the cluster labelling. For the gold-standard we use the predicted constituent categories from a tree-bank parser on the target side (English). Many phrases are not constituents, and therefore the parser output does not include their category; We exclude such phrases from the evaluation. The conditional entropy measures the amount of surprise at seeing the gold standard categories given that we know the clusters. If the cluster labels closely resemble the syntax, then there will be little surprise and the entropy will be low. If however the clusters do not match the syntax at all entropy will be very high. The conditional entropy is formulated as follows: -\[ H(S|Z) = \sum_{s,z} p(s,z) \log \frac{p(z)}{p(s,z)} \] -where $s$ are the constituent labels as output from a parser, $p(s,z)$ is the frequency of $s$ and $z$ labelling the same edge and $p(z)$ is the frequency of label $z$. If the clustering maps perfectly onto the syntax, then $z$ will always coocur with $s$ and the $\log$ term will vanish, resulting in a conditional entropy of zero. This metric can be gamed by using a separate category for every edge, and thereby still realising a perfect mapping but without any intelligent clustering at all. This degeneracy is not relevant for our models as we limit ourselves to small label sets, typically using $K = 25$ which is considerably fewer than the hundred or so syntactic categories in a treebank parser. - -%%% Local Variables: -%%% mode: latex -%%% TeX-master: "report" -%%% End: diff --git a/report/training.tex b/report/training.tex deleted file mode 100644 index 6a9e5c52..00000000 --- a/report/training.tex +++ /dev/null @@ -1,236 +0,0 @@ -\chapter{Training} - -An integral part of constructing a state-of-the-art machine translation system is the training procedure. The goal of training is to optimize the model parameters to maximize translation quality on some metric, where the parameters are the weights associated with the features we use in our model, and the metric is BLEU. - -The most common approach to training is Minimum Error Rate Training (MERT)~\cite{och:03}, which tunes the parameters to minimize error according to an arbitrary error function. Thus, in our case this is equivalent to saying that it maximizes the 1-best translation under the BLEU metric. MERT is a log-linear model which allows us to combine different features in order to find the best target translation $e*$ for a input source $f$: -$$e* = \arg\max e p(e|f) = argmax_e \sum_{k=1}^K w_kh_k(e,f)$$ - -where $h_k(e,f)$ is a feature associated with the translation of $f$ to $e$, and $w$ is the weight associated with that feature. Unfortunately, MERT has been empirically unable to extend beyond optimization of a handful of features, thus necessecitating dense features. Theses features typically include: - -\begin{itemize} -\item rule relative frequency $P(e|f)$ -\item target $n$-gram language model $P(e)$ -\item `pass-through' penalty when passing a source word to the target side untranslated -\item lexical translation probabilities $P_{lex}(\overline{e}|\overline{f})$ and $P_{lex}(\overline{f}|\overline{e})$ -\item count of the number of times that arity-0,1, or 2 SCFG rules were used -\item count of the total number of rules used -\item source word penalty -\item target word penalty -\item count of the number of times the glue rule is used -\end{itemize} - -However, after the creation of the refined grammars which have been described in the previous sections, we have additional information available to us which we would like to leverage in order to improve translational performance. The way in which we would like to utilize this informaiton is by extracting it as features for our model. For instance, some features of particular instance may be: - -\section{Feature Extraction} -There are a number potentially useful features we could extract from the refined grammars, such as: -\begin{itemize} -\item Source Syntactic Features -\item Target Syntactic Features -\item Source Context Features -\item OOV -\item Glue Rule -\item Morphology -\end{itemize} - - -\subsection{Source Syntactic Features} - -Recent work with syntax-based systems which parse the source side with a previously trained supervised parser has shown that utilizing syntactic patterns can lead to substantial improvements. Such patterns can be especially useful in capturing long-range reordering patterns, and other high-level phenomena that we are otherwise unable to leverage. Figure~\ref{fig:synt_feat1} shows an example syntactic pattern, which captures the application of rule $X_{12}$ expanding to $X_{17}X_{25}$. Although this rule may not be particularly interesting, as the translation stays monotonic. - -\begin{figure}[h] - \centering - \includegraphics[scale=0.5]{training_img_files/synt_feat1.PNG} - \caption{Syntactic Feature} - \label{fig:synt_feat1} -\end{figure} - -A more interesting example is presented in Figure~\ref{fig:synt_feat2}, where we can observe a large reodering taking place as $X_1$ expands to $X_6X_19$ and the latter moves to the left of the former. - -\begin{figure}[h] - \centering - \includegraphics[scale=0.5]{training_img_files/synt_feat2.PNG} - \caption{Syntactic Reordering Feature} - \label{fig:synt_feat2} -\end{figure} - - -\subsection{OOV} -Although we will always encounter Out-of-Vocabulary terms, we may be able to utilize the finer-grained categories to capture syntactic distribution patterns associated with each category to learn how to process the OOV terms. This may be particularly useful for numbers, nouns such as Proper names, or certain adjectives, which tend to cluster togther, as shown in Figure~\ref{fig:oov_feat}. - -\begin{figure}[h] - \centering - \includegraphics[scale=0.5]{training_img_files/oov_feat.PNG} - \caption{OOV Feature} - \label{fig:oov_feat} -\end{figure} - -\subsection{Glue Rule} -In our current system, we have one dense feature for all Glue rule applications, however, there are in fact two seperate applications which we would like to distinguish. The first occurs when a top-level $S$ node expands to one of the $X_n$ categories in the grammar, as shown in Figure~\ref{fig:glu_feat}. The second occurs when an $S$ expands to another $S$ and one of the $X_n$ categories, as in Figure~\ref{glu_feat2}. Both of these features attempt to capture the high-level derivation structure of a sentence. - -\begin{figure}[h] - \centering - \includegraphics[scale=0.5]{training_img_files/glu_feat.PNG} - \caption{Glue Rule Expansion Feature} - \label{fig:glu_feat} -\end{figure} - - -\begin{figure}[h] - \centering - \includegraphics[scale=0.5]{training_img_files/glu_feat2.PNG} - \caption{Glue Rule Combination Feature} - \label{fig:glu_feat2} -\end{figure} - -\subsection{Backoff} -Given that we have achieved significant gains from incorporating the hierarchical-bacoff feature as a dense feature, it may also be useful to add a sparser version in additional to or in place of the feature we currently use, of the form shown in Figure~\ref{fig:back_feat}. - - -\begin{figure}[h] - \centering - \includegraphics[scale=0.5]{training_img_files/back_feat.PNG} - \caption{Backoff Feature} - \label{fig:back_feat} -\end{figure} - -\section{Training Algorithms} - -As we are interested in incorporating numerous features into our model to directly help translation, we want to perform discriminative training. Given the fact that MERT is unable to optimize the sparse features we are interested in, in this workshop we investigated two alternative methods which allow us to train a model with a high dimensional feature space. The two approaches were the Margin Infused Relaxed Algorithm (MIRA)~\cite{mira:05} and Expected BLEU. All three optimization algorithms perform inference over the hypergraph, but as Table~\ref{tab:comp} shows, they are performing in quite different ways. MERT aims to optimize parameters to maximize the 1-best BLEU, or alternatively to minimize the error, by constructing a piece-wise linear error surface from the entire tuning set and performing a line search in order to find the appropriate weights. The primary limitation of this, which is responsible for its inability to scale, is the unknown diretion of the line search. When done in a handful of dimensions, random directions work relatively well, however, as we increase the feature space this becaomes a severe problem. - -Expected BLEU training, explained in detail in Section~\ref{sec:exp_bleu} is a probabilistic method which can be seen as an attempt to address some of these shortcomings. If instead of maximizing the 1-best hypothesis, as we do with MERT, we try to maximize the expected BLEU over all the hypotheses, we create a continuous, and therefore differentiable function for optimization which allows us to use gradient-based methods, such as L-BFGS. - -MIRA training, on the other hand, is a large-margin based training method, which attempts to miminimze the loss augmented score of hypotheses against some reference translation in an online fashion. In order to do so, we need to solve a Quadratic optimization problem with linear constraints, which can be handled by a technique such as Sequential Minimal Optimization (SMO). The foremost downside of this approach is the approximation of the reference that needs to take place for the training to proceed. Since the MT grammar may not contain the necessary rules to produce the correct reference translation, therefore making the translation unreachable, we need to rely on an approximation of the reference. Previous work has explred various approaches for this, such as updating toward the model 1-best, or oracle 1-best. Another possibility is that there may be multiple derivations which lead to the same translation, therefore creating ambiguity regarding which rules, and features should be updated towards. We will expand on this in Section~\ref{sec:mira}. - -\begin{table*}[htb] - \centering - \begin{tabular}{|c|c|c|c|} - & MERT & MIRA & Expected BLEU \\ \hline - Type & 1-best & Margin-based & Probabilistic \\ \hline - Objective & Minimize error & Minimize loss augmented score & Minimize expected error \\ \hline - Optimization & Line search & QP & Gradient Based \\ \hline - Limitations & Direction of search unknown & Approximation of reference & Approximate expectation \\ \hline - \end{tabular} - \caption{Training Comparison} - \label{tab:TrainingComparison} -\end{table*} - -\section{Margin Infused Relaxed Algorithm} -\label{sec:mira} - -MIRA was first introduced in 2003 by Crammer and Singer for the multi-class classification problem as a perceptron like algorithm, with the additional of a classifcation margin to reduce generalization error. This was later expanded by Taskar to structured value prediction problems, such as dependency parsing. It was notably applied to machine translation by Watanabe, and then Chiang, on whose work we build here~\cite{watanabe:07,chiang:2009:naacl}. - -\subsection{Learning Algorithm} -The basic online learning algorithm proceeds as in Algorithm~\ref{alg1}. We go through the data for $n$ iterations, and during each iteration we go through all our data points and update the weight vector after each example. We then use the new weight vector to process the next example, and so on, until we reach some convergence criteria. After convergence, we average over the weight vectors to produce a final weight vector which we can use to process new examples. The averaging of the weight vector is done to reduce overfitting, and has proved effective in previous applications. - -\begin{algorithm} -\begin{algorithmic} -\STATE Training data: $D=(x,y)$ -\STATE $weight_0=0, total=0, c=0$ -\FOR { $i= 1 \rightarrow n $} - \FOR {$d= (x,y)\in D$} - \STATE $weight_{c+1}$=update $weight_c$ with $d$ - \STATE $total=total+weight_{c+1}$ - \STATE $c=c+1$ -\ENDFOR -\ENDFOR - -\STATE $weight_{final} = \frac{total}{n \times size(D)}$ -\end{algorithmic} -\caption{Basic Online Training Algorithm} -\label{alg1} - -\end{algorithm} - -When performing inference over the hypergraph, each edge in the hypergraph corresponds to a partial translation and has associated with it a decomposable score $s$: -$$s(edge_i) = w*f(edge_i)$$ -which is comprised of the features on that edge and the current weight vector. These can then be added together to produce the score associated with a specific hypothesis translation: -$$\sum_{edge \in derivation} s(edge)= S(e) $$ - -We also compute a decomposable loss at each edge,which is the approximate BLEU score of the partial hypothesis on the edge. -What we want is to learn $w$ such that the correct output translation is given a higher score than the incorrect ones. The MIRA update does this optimization by keeping the norm of the change of the weights as small as possible -$$ min ||w_{i+1} - w_i||$$ -subject to the margin constraints, which take the following form: -$$ s(x,y) - s(x,z) \geq Loss(y,z), \forall{z} \in label(x)$$ - -Essentially, these margin constraints force us to create a margin between the correct instance y, and the incorrect instance z which is at least as large as the Loss of z. - - - - -\subsection{Oracle Extraction} -In multi-class classification, we can form the constraint set by looking at all the possible labels of x, however, in structured prediction, this becomes infeasible. Thus, in practice previous work has resorted to approximating the constraint set by performing k-best extraction over the trees in dependency parsing, or translations in MT, using only these top $k$ labels as constraints in training. This leads to the modified training algorithm of k-best MIRA, described in Algorithm~\ref{alg2}. - - - - -\begin{algorithm} -\begin{algorithmic} -\STATE Training data: $D=(e,f)$ -\STATE $weight_0=0, total=0, c=0$ -\FOR { $i= 1 \rightarrow n $} - \FOR {$d= (e,f)\in D$} - \STATE Generate $kbest(f) = \left\{e...e_k\right\}$ - \STATE Generate margin constraints $\forall e\in kbest(f)$ - \STATE $weight_{c+1}$=update $weight_c$ with $d$ - \STATE $total=total+weight_{c+1}$ - \STATE $c=c+1$ -\ENDFOR -\ENDFOR - -\STATE $weight_{final} = \frac{total}{n \times size(D)}$ -\end{algorithmic} -\caption{k-best MIRA Online Training Algorithm} -\label{alg2} - -\end{algorithm} - -For MT, recent work has shown significant improvements from obtaining three different sets of k-best lists. The first is the model k-best -$$w*f(e) $$ - the second is the model+BLEU, also referred to as the oracle or hope hypothesis The first translation in this k-best set is the oracle translation toward which we update: - $$w*f(e) + BLEU $$ - and the third is model-BLEU, or the feat hypothesis: - $$w*f(e) - BLEU $$ - - -The impetus behind updating toward towards a combination of the model and BLEU as the oracle translation is that some translations may have an excellent BLEU score, but a distant model score from the area in which most good translation reside, and parroting Voltaire, we do not want to the perfect to be the enemy of the good. - -The reasoning behind the third set of k-best lists is that the constraints we care most about for learning are the ones where our system believes the hypothesis is a good one, and thus assigns it a high score, while the BLEU score is poor, thus proving in fact to be a poor translation. - -\subsection{Online Updating} -In order to efficiently train an online learning, significant modifications were necessary to our existing parallelization framework. As updating the weight vector after each example may be inadvisable since the weights could suffer significant jumping around, we could perform mini-batch updating, where weights are only updated after a certain amount of examples have been processed. An alternative which is similar in spirit is to run several learners in parallel, and have them share their k-best hypotheses sets between themselves, in order for each learner to incorporate more information at each update. Figure ~\ref{fig:update1} presents three learners receiving a sentence in parallel. Each learner has its own MIRA trainer and decoder, with its own feature weight vector. In Figure ~\ref{fig:update2} we see Learner 1 completing its decoding of the sentence with its current weight vector, and generating the three k-best lists as described above. It then uses these to update its weights for decoding the next sentence. In Figure ~\ref{fig:update3} we see that both Learner 1 and 2 have completed decoding and generate their respective k-best lists, and these are passed to Learner 3 in order for it to incorporate them, as well as it's own set of k-best lists, when it updates its weight vector. - -\begin{figure}[h] - \centering - \includegraphics[scale=0.5]{training_img_files/update1.PNG} - \caption{Online Udpating 1)} - \label{fig:update1} -\end{figure} - - -\begin{figure}[h] - \centering - \includegraphics[scale=0.5]{training_img_files/update2.PNG} - \caption{Online Udpating 2)} - \label{fig:update2} -\end{figure} - - -\begin{figure}[h] - \centering - \includegraphics[scale=0.5]{training_img_files/update3.PNG} - \caption{Online Udpating 3)} - \label{fig:update3} -\end{figure} - -\section{Expected BLEU} -\label{sec:exp_bleu -} -\section{Accomplishments} -During the workshop, we succeeded in completely implementing MIRA and Expected BLEU training in Joshua and cdec, two state-of-the-art open source decoders. This includes the ability to extract oracles from the lattices, as well as the online updating parallelization architecture. Due to a lack of time and resources, we were unfortunatley unable to run the full suite of experiments which we had hoped for, but we leave these as immediate future work. - -\section{Future Work} -The first set of experiments concerns a standardized comparison of MIRA and Expected BLEU training, using as-close-as-possible simliar grammas, features, and data sets. To the best of our knowledge, a systematic comparison of these two popular training algorihtms has not been performed, and would be of benefit to the community. - -Second, we are interested in the language invariability of the parameters, number of iterations, and so forth for these algorthims. - - diff --git a/report/training_img_files/back_feat.PNG b/report/training_img_files/back_feat.PNG deleted file mode 100644 index 9c2efea7..00000000 Binary files a/report/training_img_files/back_feat.PNG and /dev/null differ diff --git a/report/training_img_files/glu_feat.PNG b/report/training_img_files/glu_feat.PNG deleted file mode 100644 index cc8317f5..00000000 Binary files a/report/training_img_files/glu_feat.PNG and /dev/null differ diff --git a/report/training_img_files/glu_feat2.PNG b/report/training_img_files/glu_feat2.PNG deleted file mode 100644 index dc7f4b5b..00000000 Binary files a/report/training_img_files/glu_feat2.PNG and /dev/null differ diff --git a/report/training_img_files/oov_feat.PNG b/report/training_img_files/oov_feat.PNG deleted file mode 100644 index 60c52cbf..00000000 Binary files a/report/training_img_files/oov_feat.PNG and /dev/null differ diff --git a/report/training_img_files/synt_feat1.PNG b/report/training_img_files/synt_feat1.PNG deleted file mode 100644 index f16f115a..00000000 Binary files a/report/training_img_files/synt_feat1.PNG and /dev/null differ diff --git a/report/training_img_files/synt_feat2.PNG b/report/training_img_files/synt_feat2.PNG deleted file mode 100644 index 449085ae..00000000 Binary files a/report/training_img_files/synt_feat2.PNG and /dev/null differ diff --git a/report/training_img_files/update1.PNG b/report/training_img_files/update1.PNG deleted file mode 100644 index 5604f9c2..00000000 Binary files a/report/training_img_files/update1.PNG and /dev/null differ diff --git a/report/training_img_files/update2.PNG b/report/training_img_files/update2.PNG deleted file mode 100644 index 1ccc9a7b..00000000 Binary files a/report/training_img_files/update2.PNG and /dev/null differ diff --git a/report/training_img_files/update3.PNG b/report/training_img_files/update3.PNG deleted file mode 100644 index fb332871..00000000 Binary files a/report/training_img_files/update3.PNG and /dev/null differ diff --git a/report/urdu_example_translation.graffle b/report/urdu_example_translation.graffle deleted file mode 100644 index ec3da74d..00000000 --- a/report/urdu_example_translation.graffle +++ /dev/null @@ -1,1481 +0,0 @@ - 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ZAAAAAAAAAYQAACcngAAAADGQ4SAAAAAAAAAAAAAAAAAAAAAAA== - - ReadOnly - NO - RowAlign - 1 - RowSpacing - 36 - SheetTitle - Canvas 1 - SmartAlignmentGuidesActive - YES - SmartDistanceGuidesActive - YES - UniqueID - 1 - UseEntirePage - - VPages - 1 - WindowInfo - - CurrentSheet - 0 - ExpandedCanvases - - - name - Canvas 1 - - - Frame - {{18, 22}, {1147, 750}} - ListView - - OutlineWidth - 142 - RightSidebar - - ShowRuler - - Sidebar - - SidebarWidth - 120 - VisibleRegion - {{-103, -29}, {1012, 596}} - Zoom - 1 - ZoomValues - - - Canvas 1 - 1 - 1 - - - - saveQuickLookFiles - YES - - diff --git a/report/urdu_example_translation.pdf b/report/urdu_example_translation.pdf deleted file mode 100644 index 32be1ab7..00000000 Binary files a/report/urdu_example_translation.pdf and /dev/null differ diff --git a/report/vest_mira_hope_direction/README b/report/vest_mira_hope_direction/README deleted file mode 100644 index 44dccc6f..00000000 --- a/report/vest_mira_hope_direction/README +++ /dev/null @@ -1,23 +0,0 @@ -First column = tune iteration, second column = tune BLEU - -Choosing the average of a few random sentence's model->hope direction, With Vlad's default --bleu_weight=1, nothing improved, and convergenced seemed to be slower, which is the opposite of what we intended. 5 random directions and the orthogonal directions were still used (fewer than normal random directions; the oracle directions replaced some of them). - -dev.bleu.baseline.txt - usual search directions (orth+random) - -dev.bleu.oracle_mira_direction.txt - as above, but fewer random directions, 10 model->hope directions - -note that the search directions are recomputed after each MERT iteration. - -/home/jgraehl/tune/urdu/vest-dth-oracle* - -~/tune/urdu$ ls -d vest-dth* -vest-dth vest-dth-oracle vest-dth-oracle-bleuwt=0.1 vest-dth-oracle-bleuwt=10 vest-dth-oracle-bleuwt=100 - -oraclewt devtest-estimated-BLEU -0 22.01 (orth. dirs, 10 random dirs) -0.1 22.13 (orth. dirs, 10+10 model->hope and fear->hope random directions, 5 purely random dirs) -1 22.06 " -10 21.85 " -100 22.08 " - -no evidence of any advantage using oracle directions (TODO: decode mt09 as test set, check for any advantage when using many features) diff --git a/report/vest_mira_hope_direction/dev.bleu.baseline.txt b/report/vest_mira_hope_direction/dev.bleu.baseline.txt deleted file mode 100644 index 2cf5a023..00000000 --- a/report/vest_mira_hope_direction/dev.bleu.baseline.txt +++ /dev/null @@ -1,23 +0,0 @@ -1 0.18892 -2 0.192939 -3 0.193087 -4 0.19316 -5 0.211582 -6 0.213164 -7 0.214736 -8 0.2164 -9 0.217853 -10 0.21972 -11 0.221133 -12 0.221733 -13 0.222067 -14 0.222347 -15 0.220126 -16 0.220623 -17 0.220766 -18 0.220915 -19 0.220979 -20 0.22119 -21 0.221739 -22 0.22174 -23 0.221802 diff --git a/report/vest_mira_hope_direction/dev.bleu.oracle_mira_direction.txt b/report/vest_mira_hope_direction/dev.bleu.oracle_mira_direction.txt deleted file mode 100644 index f6cd4972..00000000 --- a/report/vest_mira_hope_direction/dev.bleu.oracle_mira_direction.txt +++ /dev/null @@ -1,39 +0,0 @@ -1 0.189294 -2 0.193352 -3 0.194648 -4 0.194931 -5 0.195066 -6 0.21277 -7 0.214142 -8 0.214968 -9 0.215563 -10 0.215798 -11 0.216671 -12 0.217189 -13 0.217404 -14 0.21743 -15 0.217222 -16 0.217487 -17 0.217598 -18 0.217633 -19 0.216885 -20 0.217254 -21 0.218321 -22 0.219699 -23 0.2204 -24 0.220668 -25 0.220817 -26 0.220831 -27 0.220091 -28 0.220761 -29 0.220872 -30 0.220923 -31 0.220602 -32 0.220661 -33 0.221046 -34 0.221234 -35 0.221252 -36 0.220876 -37 0.220985 -38 0.220989 -39 0.221083 diff --git a/report/viewer/PMingLiU.ttf b/report/viewer/PMingLiU.ttf deleted file mode 100644 index 03e923bf..00000000 Binary files a/report/viewer/PMingLiU.ttf and /dev/null differ diff --git a/report/viewer/alignment.py b/report/viewer/alignment.py deleted file mode 100644 index 5fe03734..00000000 --- a/report/viewer/alignment.py +++ /dev/null @@ -1,162 +0,0 @@ -class Alignment: - SURE, POSSIBLE = 'S', 'P' - - def __init__(self, swords, twords, align): - self.swords = swords - self.twords = twords - self.align = align - - def reverse(self): - als = {} - for (frm, to), conf in self.align.items(): - als[to, frm] = conf - return Alignment(self.twords, self.swords, als) - - def merge(self, other): - assert self.swords == other.swords - assert self.twords == other.twords - - als = {} - for frm, to in self.align.keys(): - als[frm, to] = Alignment.POSSIBLE - - for frm, to in other.align.keys(): - if (frm, to) in als: - als[frm, to] = Alignment.SURE - else: - als[frm, to] = Alignment.POSSIBLE - - return Alignment(self.swords, self.twords, als) - - def __repr__(self): - return 'Alignment(swords=%s, twords=%s, align=%s)' % (self.swords, self.twords, self.align) - -def read_pharaoh_text(infile): - return infile.readline().strip().split() - -def parse_pharaoh_align(text): - als = {} - for part in text.strip().split(): - frm, to = map(int, part.split('-')) - als[frm, to] = Alignment.SURE - return als - -def read_pharaoh_align(infile): - als = {} - for part in infile.readline().strip().split(): - frm, to = map(int, part.split('-')) - als[frm, to] = Alignment.SURE - return als - -def read_pharaoh_alignment(swfile, twfile, afile): - sw = read_pharaoh_text(swfile) - tw = read_pharaoh_text(twfile) - als = read_pharaoh_align(afile) - return Alignment(sw, tw, als) - -def read_giza_alignment(infile): - infile.readline() # ignore - swords = infile.readline().strip().split() - twords = [] - als = {} - state = 0 - for token in infile.readline().strip().split(): - if state == 0: - if token != 'NULL': - if token != '({': - twords.append(token) - else: - state = 1 - elif state == 1: - if token != '})': - if twords: - als[int(token)-1, len(twords)-1] = Alignment.SURE - else: - state = 0 - return Alignment(swords, twords, als) - -def read_naacl_aligns(infile): - aligns = [] - last = None - for line in infile: - index, frm, to, conf = line.rstrip().split() - if int(index) != last: - aligns.append({}) - aligns[-1][int(frm)-1, int(to)-1] = conf - last = int(index) - return aligns - -# -# This phrase-extraction function largely mimics Pharaoh's phrase-extract -# code. It also supports the option to not advance over NULL alignments. -# - -def xextract_phrases(alignment, maxPhraseLength=None, advance=True): - T = len(alignment.twords) - S = len(alignment.swords) - if not maxPhraseLength: - maxPhraseLength = max(T, S) - - alignedCountS = [0 for s in alignment.swords] - alignedToT = [[] for t in alignment.twords] - alignedToS = [[] for s in alignment.swords] - for (s, t), conf in alignment.align.items(): - if conf == Alignment.SURE: - alignedCountS[s] += 1 - alignedToT[t].append(s) - alignedToS[s].append(t) - - # check alignments for english phrase startT...endT - for st in range(T): - for et in range(st, min(T, st + maxPhraseLength)): - minS = 9999 - maxS = -1 - usedS = alignedCountS[:] - for ti in range(st, et+1): - for si in alignedToT[ti]: - #print 'point (%d, %d)' % (si, ti) - if simaxS: maxS = si - usedS[si] -= 1 - - #print 's projected (%d-%d, %d, %d)' % (minS, maxS, st, et) - if (maxS >= 0 and # aligned to any foreign words at all - maxS-minS < maxPhraseLength): # foreign phrase within limits - # check if foreign words are aligned to out of bound english words - out_of_bounds = False - for si in range(minS, maxS): - if usedS[si] > 0: - #print 'out of bounds:', si - out_of_bounds = True - break - - # Pharoah doesn't use this check, but I think it's required - if not out_of_bounds: - for s in range(minS, maxS+1): - for t in alignedToS[s]: - if not (st <= t <= et): - #print 'out of bounds2:', t,s - out_of_bounds = True - break - - #print 'doing it for (%d-%d, %d, %d)' % (minS, maxS, st, et) - if not out_of_bounds: - if advance: - #print 'attempting to advance' - # start point of foreign phrase may advance over unaligned - ss = minS - while (ss>=0 and - ss>maxS-maxPhraseLength and # within length limit - (ss==minS or alignedCountS[ss]==0)): # unaligned - # end point of foreign phrase may advance over unaligned - es = maxS - while (es>sys.stderr, 'WARNING: replacing existing flowable' - self._body = flowable - - def render(self): - self._body.canv = self._canvas - width, height = self._body.wrap(*self._size) - width *= 1.02 - height *= 1.02 - - self._canvas = canvas.Canvas(self._filename, (width, height)) - self._body.canv = self._canvas - self._body.draw() - self._canvas.save() -- cgit v1.2.3