ECAI 2004 Conference Paper

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Similarity-based ontology alignment in OWL-Lite

Jérôme Euzenat, Petko Valtchev

Interoperability of heterogeneous systems on the Web will be admittedly achieved through an agreement between the underlying ontologies. However, the richer the ontology description languages, the more complex the agreement process, and hence the more sophisticated the corresponding tools. We believe that among current ontology alignment paradigms, similarity-based approaches are both powerful and flexible enough to adapt to the alignment within ontology languages like OWL. Our own approach amounts to defining a universal measure for comparing the entities of two ontologies that is based on a simple and homogeneous comparison principle. Instead of using the external textual form, our similarity works on a dedicated graph representation where ontology (language) entities become (typed) vertices and their relationships (typed) edges, and where a vertex is basically described through its adjacent edges. As one-to-many relationships and circularity in inter-entity dependencies constitute the key difficulties in the resulting context, we insist on the related topics in the similarity definition and computation while illustrating them through an example.

Keywords: Ontologies, Reuse of Knowledge, Machine Learning

Citation: Jérôme Euzenat, Petko Valtchev: Similarity-based ontology alignment in OWL-Lite. In R.López de Mántaras and L.Saitta (eds.): ECAI2004, Proceedings of the 16th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2004, pp.323-327.

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ECAI-2004 is organised by the European Coordinating Committee for Artificial Intelligence (ECCAI) and hosted by the Universitat Politècnica de València on behalf of Asociación Española de Inteligencia Artificial (AEPIA) and Associació Catalana d'Intel-ligència Artificial (ACIA).