A context expansion method for supervised word sense disambiguation

Francisco Tacoa, Danushka Bollegala, Mitsuru Ishizuka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Feature sparseness is one of the main causes for Word Sense Disambiguation (WSD) systems to fail, as it increases the probability of incorrect predictions. In this work, we present a WSD method to overcome this problem by using an automatically-created thesaurus to append related words to a specific context, in order to improve the effectiveness of candidate selection for an ambiguous word. We treat the context as a vector of words taken from sentences, and expand it with words from the thesaurus according to their mutual relatedness. Our results suggest that the method performs disambiguation with high precision.

Original languageEnglish
Title of host publicationProceedings - IEEE 6th International Conference on Semantic Computing, ICSC 2012
Pages339-341
Number of pages3
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event6th IEEE International Conference on Semantic Computing, ICSC 2012 - Palermo
Duration: 2012 Sep 192012 Sep 21

Other

Other6th IEEE International Conference on Semantic Computing, ICSC 2012
CityPalermo
Period12/9/1912/9/21

ASJC Scopus subject areas

  • Software

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