A framework for evaluating ontology meta-matching approaches

Abstract

Ontology matching has become a key issue to solve problems of semantic heterogeneity. Several researchers propose diverse techniques that can be used in distinct scenarios. Ontology meta-matching approaches are a specialization of ontology matching and have achieved good results in pairs of ontologies with different types of heterogeneities. However, developing a new ontology meta-matcher can be a costly process and a lot of experiments are often carried out to analyze the behavior of the matcher. This article presents a modularized framework that covers the main stages of the ontology meta-matching evaluation process. This framework aims to aid researchers to develop and analyze algorithms for ontology meta-matching, mainly metaheuristic-based supervised and unsupervised approaches. As the main contribution of the research, the framework proposed will facilitate the evaluation of ontology meta-matching approaches and, as the secondary contribution, a data provenance model that captures the main information generated and consumed throughout experiments is presented in the framework.

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Notes

  1. 1.

    https://www.w3.org/ns/prov

  2. 2.

    https://www.w3.org/

  3. 3.

    https://www.w3.org/TR/2013/REC-prov-o-20130430/

  4. 4.

    http://oaei.ontologymatching.org/

  5. 5.

    https://bitbucket.org/nicolasferranti/heuristicontologymatching/src/master/

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Correspondence to Nicolas Ferranti.

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Ferranti, N., Mouro, J.R., Mendonça, F.M. et al. A framework for evaluating ontology meta-matching approaches. J Intell Inf Syst (2020). https://doi.org/10.1007/s10844-020-00615-8

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Keywords

  • Ontology matching
  • Evolutionary ontology matching
  • Ontology meta-matching
  • Metaheuristics
  • Data provenance