Effect of semantic differences in WordNet-based similarity measures

Authors:
Raúl Ernesto Menéndez-Mora;Ryutaro Ichise
Affiliations:
National Institute of Informatics, Tokyo, Japan and Facultad de Informática y Matemática, Universidad de Holguín, Holguín, Cuba;National Institute of Informatics, Tokyo, Japan
Venue:
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
Year:
2010

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Abstract

Assessing the semantic similarity of words is a generic problem in many research fields such as artificial intelligence, biomedicine, linguistics, cognitive science and psychology. The difficulty of this task lies in how to find an effective way to simulate the process of human judgement of word similarity. In this paper, we introduce the idea of semantic differences and commonalities between words to the similarity computation process. Five new semantic similarity metrics are obtained after applying this scheme to traditional WordNet-based measures. In an experimental evaluation of our approach on a standard 28 word pairs dataset, three of the measures outperformed their classical version, while the other two performed as well as their unmodified counterparts.