Difference between revisions of "User:Deadbeef/LexicalSelection"
m (srl and slr) |
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the context <math>c</math> could be a text frame, a bag of words, a tfidf-labelled array etc. |
the context <math>c</math> could be a text frame, a bag of words, a tfidf-labelled array etc. |
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the possible translations for w can be obtained maybe |
the possible translations for w can be obtained maybe from WordNet? or another dictionary? |
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{{comment|We already have a set of attributes (<code>srl</code> and <code>slr</code>) to mark ambiguous words; it would be best to use those. en-ca and en-es have examples -- [[User:Jimregan|Jimregan]] 13:22, 21 June 2009 (UTC)}} |
{{comment|We already have a set of attributes (<code>srl</code> and <code>slr</code>) to mark ambiguous words; it would be best to use those. en-ca and en-es have examples -- [[User:Jimregan|Jimregan]] 13:22, 21 June 2009 (UTC)}} |
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{{comment|Awesome :D I'll give it a read in the next days :) Thanks a lot! -- [[User:Deadbeef|Deadbeef]] 23:53, 30 June 2009 (UTC)}} |
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the classification problem can be solved in various ways: support vector machines, naive-bayes classifier, decision tree etc. |
the classification problem can be solved in various ways: support vector machines, naive-bayes classifier, decision tree etc. |
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It seems that the WSD problem can be handled with a Inductive Logic Programming-oriented approach, as this paper states: http://www.mt-archive.info/ACL-2007-Specia.pdf |
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I'm currently trying to introduce probabilistic reasoning into Aleph - the Inductive Logic Programming framework cited in the paper - for a university project, it would be interesting to see how it performs with lexical selection :) I'll commit some code when I get it to work :D |
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Aleph can be found here: http://www.comlab.ox.ac.uk/activities/machinelearning/Aleph/aleph_toc.html - BEWARE: it's written in Prolog |
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= Some Bookmarks (please feel free to add more) = |
= Some Bookmarks (please feel free to add more) = |
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Revision as of 21:49, 30 June 2009
Introduction
Feel free to edit/comment/spam/anything here
Some formalizing
IMHO the LS problem can be reduced to a classification problem:
the context could be a text frame, a bag of words, a tfidf-labelled array etc.
the possible translations for w can be obtained maybe from WordNet? or another dictionary?
We already have a set of attributes (srl and slr) to mark ambiguous words; it would be best to use those. en-ca and en-es have examples -- Jimregan 13:22, 21 June 2009 (UTC)
Awesome :D I'll give it a read in the next days :) Thanks a lot! -- Deadbeef 23:53, 30 June 2009 (UTC)
the classification problem can be solved in various ways: support vector machines, naive-bayes classifier, decision tree etc.
It seems that the WSD problem can be handled with a Inductive Logic Programming-oriented approach, as this paper states: http://www.mt-archive.info/ACL-2007-Specia.pdf
I'm currently trying to introduce probabilistic reasoning into Aleph - the Inductive Logic Programming framework cited in the paper - for a university project, it would be interesting to see how it performs with lexical selection :) I'll commit some code when I get it to work :D
Aleph can be found here: http://www.comlab.ox.ac.uk/activities/machinelearning/Aleph/aleph_toc.html - BEWARE: it's written in Prolog
Some Bookmarks (please feel free to add more)
Using UMLS Concept Unique Identifiers (CUIs) for Word Sense Disambiguation in the Biomedical Domain: http://www.d.umn.edu/~tpederse/Pubs/amia07.pdf
Word Sense Disambiguation - Algorithms and Applications: http://www.wsdbook.org/
Word Sense Disambiguation: The State of the Art: http://sites.univ-provence.fr/~veronis/pdf/1998wsd.pdf
Word Sense Disambiguation (slide from the "Linguaggi e Traduttori" class): http://www.di.uniba.it/~semeraro/LT/WSD.pdf
Perl scripts doing WSD and mapping on UMLS ontologies: http://cuitools.sourceforge.net/
Nice ACM survey on WSD: http://www.dsi.uniroma1.it/~navigli/pubs/ACM_Survey_2009_Navigli.pdf
Verb Semantics and Lexical Selection: http://www.ldc.upenn.edu/acl/P/P94/P94-1019.pdf
