Abstract

Ontologies aim at providing a formal, explicit and shared conceptualization and understanding of common domains between different communities. However, the distributed nature of ontology development resulted in the semantic heterogeneity between ontologies. Semantic heterogeneity constitutes the major obstacle against achieving interoperability between ontologies. To overcome this obstacle a novel method is designed for semi-automatic ontology merging. It combines syntactic and semantic measures for identifying similar concepts that will be merged in a signal one in the resulting merged ontology. The structural relationships between ontologies are solved by similarity measures. After combining the results, similar concepts are merged in a single one by normalizing the weights of all the similarity measures.

Authors and Affiliations