A similarity-based approach for ontology mapping

Ontology mapping is the key point to reach interoperability over ontologies. In semantic Web environment, ontologies are usually distributed and heterogeneous and thus it is necessary to find the mapping between them. Aiming at ontology mapping between different ontologies, a new synthesized algorithm of concept similarity is proposed in this paper. An advanced measure of setting candidate mapping set is applied to reduce the runtime of the account. The presented algorithm involves concept name, attribute, structure and instance levels. To deal with the problem of name conflict in mapping process, we use thesaurus and statistical technique. Experimental results indicate that the proposed method can significantly outperform the baseline methods, and also obtains improvement over the existing methods.