Effective Method for Large Scale Ontology Matching

Nowadays, we are facing a proliferation of heterogeneous biomedical data sources accessible through various knowledgebased applications. These data are annotated by more and more large and disseminated knowledge organization systems ranging from simple terminologies and structured vocabularies to very formal ontologies. In order to solve the interoperability issue which arises due to the heterogeneity of these ontologies, an alignment task is usually performed. However, while a significant effort has been undertaken to provide tools that automatically align ontologies containing hundreds of entities, a little attention has been paid to the matching of large size ontologies as it uses to be the case in the life sciences domain. We present in this paper ServOMap, a fast and efficient high precision system able to perform matching ontologies containing hundreds of thousands of entities. The system participated in the 2012 edition of the Ontology Alignment Evaluation Initiative campaign and achieved very good performance, among the top three systems for the Large Biomedical Ontologies Track.