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Alignment-based Partitioning of Large-scale Ontologies

Fayçal Hamdi 1, 2 Brigitte Safar 1, 2 Chantal Reynaud 1, 2 Haifa Zargayouna 2, 3
2 GEMO - Integration of data and knowledge distributed over the web
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
Abstract : Ontology alignment is an important task for information integration systems that can make different resources, described by various and heterogeneous ontologies, interoperate. However very large ontologies have been built in some domains such as medicine or agronomy and the challenge now lays in scaling up alignment techniques that often perform complex tasks. In this paper, we propose two partitioning methods which have been designed to take the alignment objective into account in the partitioning process as soon as possible. These methods transform the two ontologies to be aligned into two sets of blocks of a limited size. Furthermore, the elements of the two ontologies that might be aligned are grouped in a minimal set of blocks and the comparison is then enacted upon these blocks. Results of experiments performed by the two methods on various pairs of ontologies are promising.
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Fayçal Hamdi, Brigitte Safar, Chantal Reynaud, Haifa Zargayouna. Alignment-based Partitioning of Large-scale Ontologies. Fabrice Guillet and Gilbert Ritschard and Djamel Zighed and Henri Briand. Advances in Knowledge Discovery And Management, 292, Springer, pp.251-269, 2010, 978-3-642-00579-4. ⟨10.1007/978-3-642-00580-0⟩. ⟨inria-00432606⟩

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