Difference between revisions of "User:Deadbeef/LexicalSelection"

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:<math>\mathrm{classify}(word\ w,\ context\ c)\ \in\ \{\ m\ :\ m\ meaning\ associated\ to\ w\ \}.</math>
:<math>\mathrm{classify}(word\ w,\ context\ c)\ \in\ \{\ m\ :\ m\ meaning\ associated\ to\ w\ \}.</math>

the context <math>c</math> could be a text frame, a bag of words, a tfidf-labelled array etc.

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) =
= Some Bookmarks (please feel free to add more) =

Revision as of 14:09, 20 June 2009

Introduction

Hello world!


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 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