User:Deadbeef/LexicalSelection

Introduction

Feel free to edit/comment/spam/anything here

Some formalizing

IMHO the LS problem can be reduced to a classification problem:

$\mathrm {classify} (word\ w,\ context\ c)\ \in \ \{\ t\ :\ t\ possible\ translation\ for\ w\ \}.$

the context $c$ could be a text frame, a bag of words, a tfidf-labelled array etc.

the possible translations for w can be obtained maybe for 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)

the classification problem can be solved in various ways: support vector machines, naive-bayes classifier, decision tree etc.

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