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Considerable research in the field of ontology matching has been performed where information sharing and reuse becomes necessary in ontology development. Measurement of lexical similarity in ontology matching is performed using synset, defined in WordNet. In this paper, we defined a Super Word Set, which is an aggregate set that includes hypernym, hyponym, holonym, and meronym sets in WordNet. The Super Word Set Similarity is calculated by the rate of words of concept name and synset’s words inclusion in the Super Word Set. In order to measure of Super Word Set Similarity, we first extracted Matched Concepts(MC), Matched Properties(MP) and Property Unmatched Concepts(PUC) from the result of ontology matching. We compared these against two ontology matching tools – COMA++ and LOM. The Super Word Set Similarity shows an average improvement of 12% over COMA++ and 19% over LOM.

Ontology Matching Based on hypernym, hyponym, holonym, and meronym Sets in WordNet