Fuzzy word similarity: A semantic approach using WordNet

Sukanya Manna*, B. Sumudu U. Mendis

*Corresponding author for this work

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

    6 Citations (Scopus)

    Abstract

    In this paper we present a hybrid measure of semantic word similarity using fuzzy inference system which combines both the corpus based distance measures as well as gloss overlap to get the final similarity between two words. We use WordNet as a lexical dictionary to get semantic information about words. We show that this new measure reasonably correlates to human judgments and the average performance is boosted by using triangular membership function in the output.

    Original languageEnglish
    Title of host publication2010 IEEE World Congress on Computational Intelligence, WCCI 2010
    DOIs
    Publication statusPublished - 2010
    Event2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - Barcelona, Spain
    Duration: 18 Jul 201023 Jul 2010

    Publication series

    Name2010 IEEE World Congress on Computational Intelligence, WCCI 2010

    Conference

    Conference2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010
    Country/TerritorySpain
    CityBarcelona
    Period18/07/1023/07/10

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