文章基本信息

标题：Ontology Matching Based on hypernym, hyponym, holonym, and meronym Sets in WordNet
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作者：JungAe Kwak ; Hwan-Seung Yong
期刊名称：International Journal of Web & Semantic Technology
印刷版ISSN：0976-2280
电子版ISSN：0975-9026
出版年度：2010
卷号：1
期号：2
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：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.
关键词：Ontology Matching; Property Unmatched Concept; Semantic Relationship Set; Super Word Set Similarity