Fuzzy word similarity: A semantic approach using WordNet

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 w...

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Bibliographic Details
Published inInternational Conference on Fuzzy Systems pp. 1 - 8
Main Authors Manna, S, Mendis, B S U
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2010
Subjects
Context
Dictionaries
Fuzzy sets
Gravity
Pragmatics
Semantics
Speech
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Summary: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.
ISBN:1424469198
9781424469192
ISSN:1098-7584
DOI:10.1109/FUZZY.2010.5584785