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

    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 publicationACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference
    PublisherAssociation for Computational Linguistics (ACL)
    Pages884-893
    Number of pages10
    Volume1
    ISBN (Print)9781937284503
    Publication statusPublished - 2013
    Event51st Annual Meeting of the Association for Computational Linguistics, ACL 2013 - Sofia
    Duration: 2013 Aug 42013 Aug 9

    Other

    Other51st Annual Meeting of the Association for Computational Linguistics, ACL 2013
    CitySofia
    Period13/8/413/8/9

    Fingerprint

    performance
    linguistics
    Disambiguation
    Strings
    Word Sense
    Kernel
    Superiority
    Linguistic Context
    Conventional
    time

    ASJC Scopus subject areas

    • Language and Linguistics
    • Linguistics and Language

    Cite this

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

    Density maximization in context-sense metric space for all-words WSD. / Tanigaki, Koichi; Shiba, Mitsuteru; Munaka, Tatsuji; Sagisaka, Yoshinori.

    ACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference. Vol. 1 Association for Computational Linguistics (ACL), 2013. p. 884-893.

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

    Tanigaki, K, Shiba, M, Munaka, T & Sagisaka, Y 2013, Density maximization in context-sense metric space for all-words WSD. in ACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference. vol. 1, Association for Computational Linguistics (ACL), pp. 884-893, 51st Annual Meeting of the Association for Computational Linguistics, ACL 2013, Sofia, 13/8/4.
    Tanigaki K, Shiba M, Munaka T, Sagisaka Y. Density maximization in context-sense metric space for all-words WSD. In ACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference. Vol. 1. Association for Computational Linguistics (ACL). 2013. p. 884-893
    Tanigaki, Koichi ; Shiba, Mitsuteru ; Munaka, Tatsuji ; Sagisaka, Yoshinori. / Density maximization in context-sense metric space for all-words WSD. ACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference. Vol. 1 Association for Computational Linguistics (ACL), 2013. pp. 884-893
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