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Fuzzy Word Similarity: A Semantic Approach Using WordNet

Manna, Sukanya; Mendis, B Sumudu

Description

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.

CollectionsANU Research Publications
Date published: 2010
Type: Conference paper
URI: http://hdl.handle.net/1885/55212
Source: Proceedings of the 19th international conference on Fuzzy Systems
DOI: 10.1109/FUZZY.2010.5584785

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