An Asymmetric Similarity Measure for Ontologies Based on the Feature Contrast Model

Authors:
Watson Wei Khong Chua;Angela Eck Soong Goh
Affiliations:
-;-
Venue:
CISIS '10 Proceedings of the 2010 International Conference on Complex, Intelligent and Software Intensive Systems
Year:
2010

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Cited 2

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Abstract

Ontology alignment is a time consuming process, especially when the two ontologies to be aligned are large. A fast and accurate ontology similarity can help the user to avoid aligning ontologies without significant similarities. In this paper, we propose an Asymmetric Similarity Measure for Ontologies (ASMO) that measures how similar the source ontology is to the target ontology. Many efficient ontology similarity measures are based on syntactic similarities between entities but these measures are unable to identify concepts represented using synonyms. We introduce a Synset Clustering method (S-Clust) to measure the synonymical similarity of concepts and our experimental results show that S-Clust is able to address the limitations of syntactic similarity measures in only 1.74% of the time taken to do a pairwise synonymical similarity comparison between concepts.