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Alignment-Based Partitioning of Large-Scale Ontologies

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Advances in Knowledge Discovery and Management

Part of the book series: Studies in Computational Intelligence ((SCI,volume 292))

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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Hamdi, F., Safar, B., Reynaud, C., Zargayouna, H. (2010). Alignment-Based Partitioning of Large-Scale Ontologies. In: Guillet, F., Ritschard, G., Zighed, D.A., Briand, H. (eds) Advances in Knowledge Discovery and Management. Studies in Computational Intelligence, vol 292. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00580-0_15

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  • DOI: https://doi.org/10.1007/978-3-642-00580-0_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-00579-4

  • Online ISBN: 978-3-642-00580-0

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