A Rough Similarity Measure for Ontology Mapping

Abstract

With the development of the semantic Web and of semantic Web services an explosion in the number of ontologies employed is to be expected. How to match the concepts in different ontologies is quite an important research topic. A weighted rough ontology mapping method based on rough set theory and formal concept analysis is proposed: the two source ontologies are first transformed into formal contexts with linguistic processing techniques; then, the two formal contexts are merged to obtain a complete concept lattice; finally, a rough similarity measure is introduced to produce the ontology mapping results. The proposed similarity model is structural with a specific rough lower measure and a boundary measure, and is expected to be accurate with the help of the weights for adjusting the degree of the two obtained similarity measures' importance.