Deriving Concept Mappings through Instance Mappings

Ontology matching is a promising step towards the solution to the interoperability problem of the Semantic Web. Instance-based methods have the advantage of focusing on the most active parts of the ontologies and reflect concept semantics as they are actually being used. Previous instance-based mapping techniques were only applicable to cases where a substantial set of instances shared by both ontologies. In this paper, we propose to use a lexical search engine to map instances from different ontologies. By exchanging concept classification information between these mapped instances, an artificial set of common instances is built, on which existing instance-based methods can apply. Our experiment results demonstrate the effectiveness and applicability of this method in broad thesaurus mapping context.