Ontology alignment based on instance using NSGA-II

Nowadays, ontologies are widely used to solve data heterogeneity problems on the Semantic Web. However, simple use of these ontologies may raise the heterogeneity problem to a higher level. Addressing this problem requires identification of correspondences between the entities of various ontologies. Since the real semantics of a concept is often better defined by the actual instances assigned to it, instance, as an important element of ontology, contains a great quantity of knowledge that should be utilized to obtain the ontology alignment. To this end, in this paper, we propose a novel instance-based aligning approach using NSGA-II to determine the optimal instance correspondences and a similarity propagation algorithm that makes use of various semantic relations to propagate the similarity values to other entities of ontologies. The experiment of comparing our approach with the participants of OAEI 2012 has demonstrated that our method is an effective approach that can obtain the alignment with high precision value.