Exploring Web Semantic Knowledge and User Feedback to Improve Ontology Matching

The first step to integrate multiple data sources is to decrease the heterogeneity between their schemas. This task can be facilitated if data source schemas are represented as ontologies. In this case, ontology matching enables the identification of correspondences between elements of data source schemas. We propose an ontology matching approach to improve the accuracy of correspondences using an additional source of knowledge. We take advantage of the knowledge available on the Semantic Web obtaining an ontology to be used as background knowledge. Semantic rules are executed in order to discover new correspondences between ontology elements. Our approach also offers to the users the possibility of rejecting invalid correspondences. These rejections are stored and used on further executions of the ontology matching to remove invalid correspondences.

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