Density maximization in context-sense metric space for all-words WSD

Koichi Tanigaki, Mitsuteru Shiba, Tatsuji Munaka, Yoshinori Sagisaka

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

2 Citations (Scopus)

Abstract

This paper proposes a novel smoothing model with a combinatorial optimization scheme for all-words word sense disambiguation from untagged corpora. By generalizing discrete senses to a continuum, we introduce a smoothing in context-sense space to cope with data-sparsity resulting from a large variety of linguistic context and sense, as well as to exploit senseinterdependency among the words in the same text string. Through the smoothing, all the optimal senses are obtained at one time under maximum marginal likelihood criterion, by competitive probabilistic kernels made to reinforce one another among nearby words, and to suppress conflicting sense hypotheses within the same word. Experimental results confirmed the superiority of the proposed method over conventional ones by showing the better performances beyond most-frequent-sense baseline performance where none of SemEval-2 unsupervised systems reached.

Original languageEnglish
Title of host publicationLong Papers
PublisherAssociation for Computational Linguistics (ACL)
Pages884-893
Number of pages10
ISBN (Print)9781937284503
Publication statusPublished - 2013 Jan 1
Event51st Annual Meeting of the Association for Computational Linguistics, ACL 2013 - Sofia, Bulgaria
Duration: 2013 Aug 42013 Aug 9

Publication series

NameACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference
Volume1

Conference

Conference51st Annual Meeting of the Association for Computational Linguistics, ACL 2013
CountryBulgaria
CitySofia
Period13/8/413/8/9

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language

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    Tanigaki, K., Shiba, M., Munaka, T., & Sagisaka, Y. (2013). Density maximization in context-sense metric space for all-words WSD. In Long Papers (pp. 884-893). (ACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference; Vol. 1). Association for Computational Linguistics (ACL).