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A K-way spectral partitioning of an ontology for ontology matching

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Abstract

Ontology matching, the process of resolving heterogeneity between two ontologies consumes a lot of computing memory and time. This problem is exacerbated in large ontology matching tasks. To address the problem of time and space complexity in the matching process, ontology partitioning has been adopted as one of the methods, however, most ontology partitioning algorithms either produce incomplete partitions or are slow in the partitioning process hence eroding the benefits of the partitioning. In this paper, we demonstrate that spectral partitioning of an ontology can generate high quality partitions geared towards ontology matching.

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Notes

  1. http://sourceforge.net/projects/owlapi.

  2. https://github.com/ernestojimenezruiz/logmap-matcher.

  3. https://github.com/AgreementMakerLight/AML-Jar.

  4. http://oaei.ontologymatching.org/2016/anatomy/anatomy-dataset.zip.

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  1. Makerere University, Kampala, Uganda

    Peter Ochieng & Swaib Kyanda

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  1. Peter Ochieng
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  2. Swaib Kyanda
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Correspondence to Peter Ochieng.

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Ochieng, P., Kyanda, S. A K-way spectral partitioning of an ontology for ontology matching. Distrib Parallel Databases 36, 643–673 (2018). https://doi.org/10.1007/s10619-018-7222-8

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