Similarity aggregation in ontology matching based on reliability maximization

“Ontology matching” aims to find semantic correspondences between entities of different ontologies. Achieving semantic interoperability in building the Semantic Web highly relies on matching ontologies. It has been shown that integrating multiple individual matchers to explore different aspects of similarities between ontologies leads to better results than just using one matcher. Thus, similarity aggregation is an important and yet difficult step in developing ontology matching systems. Previously, we introduced a concept, called reliability of a similarity measure, and proposed an approach to assign weights to different similarity measures based on their reliabilities. In this paper we revise the definition of reliability and also formulate the problem of similarity aggregation as a constrained optimization. We assign weights in the range of [0, 1] to different similarity measures in a way to maximize the reliability of the aggregated similarity matrix. Experimental results showed that our aggregation method outperforms other existing ones on OAEI benchmark tests.