Unsupervised word sense disambiguation using neighborhood knowledge

Huang Heyan*, Yang Zhizhuo, Jian Ping

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

Usually ambiguous words contained in article appear several times. Almost all existing methods for unsupervised word sense disambiguation make use of information contained only in ambiguous sentence. This paper presents a novel approach by considering neighborhood knowledge. The approach can naturally make full use of the within-sentence relationship from the ambiguous sentence and cross-sentence relationship from the neighborhood knowledge. Experimental results indicate the proposed method can significantly outperform the baseline method.

Original languageEnglish
Title of host publicationPACLIC 25 - Proceedings of the 25th Pacific Asia Conference on Language, Information and Computation
Pages333-342
Number of pages10
Publication statusPublished - 2011
Event25th Pacific Asia Conference on Language, Information and Computation, PACLIC 25 - , Singapore
Duration: 16 Dec 201118 Dec 2011

Publication series

NamePACLIC 25 - Proceedings of the 25th Pacific Asia Conference on Language, Information and Computation

Conference

Conference25th Pacific Asia Conference on Language, Information and Computation, PACLIC 25
Country/TerritorySingapore
Period16/12/1118/12/11

Keywords

  • Graphbased ranking algorithm
  • Neighborhood knowledge
  • Similarity measure
  • Unsupervised WSD

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