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Fuzzy word similarity: A semantic approach using WordNet

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2 Author(s)
Manna, S. ; Inf. & Human Centered Comput. group, Australian Nat. Univ., Canberra, ACT, Australia ; Mendis, B.S.U.

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.

Published in:

Fuzzy Systems (FUZZ), 2010 IEEE International Conference on

Date of Conference:

18-23 July 2010