A context expansion method for supervised word sense disambiguation

Francisco Tacoa*, Danushka Bollegala, Mitsuru Ishizuka

*この研究の対応する著者

研究成果: Conference contribution

4 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトルProceedings - IEEE 6th International Conference on Semantic Computing, ICSC 2012
ページ339-341
ページ数3
DOI
出版ステータスPublished - 2012
外部発表はい
イベント6th IEEE International Conference on Semantic Computing, ICSC 2012 - Palermo
継続期間: 2012 9 192012 9 21

Other

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

ASJC Scopus subject areas

  • ソフトウェア

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