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A Prey–Predator Approach for Ontology Meta-matching

  • Original Article
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Journal on Data Semantics

Abstract

Ontology matching has become one of the main research topics to address problems related to semantic interoperability on the web. The main goal is to find ways to make different ontologies interoperable. Due to the high heterogeneity in the knowledge representation of each ontology, several matchers are proposed in the literature, each seeking to capture a specific aspect of the ontology. Generally, different matchers are complementary and none stand out in all test cases. In this paper, we present a meta-matching approach employing the prey–predator meta-heuristic in order to define a set of weights to find the best possible result from a set of matchers. The approach was evaluated on the Ontology Alignment Evaluation Initiative benchmark and results showed that the prey–predator algorithm is competitive with other popular algorithms as it achieves an average f-measure of 0.91.

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Notes

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

  2. http://oaei.ontologymatching.org/

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Author information

Authors and Affiliations

  1. Campus Universitário, Juiz de Fora, 36.060-900, Brazil

    Nicolas Ferranti

  2. Federal University of Juiz de Fora (UFJF), Juiz de Fora, Brazil

    Nicolas Ferranti, Jairo Francisco de Souza & Stênio Sã Rosário Furtado Soares

  3. LApIC Research Group, Departament of Computer Science, Campus Universitário, Juiz de Fora, 36.060-900, Brazil

    Jairo Francisco de Souza

  4. Departament of Computer Science, Campus Universitário, Juiz de Fora, 36.060-900, Brazil

    Stênio Sã Rosário Furtado Soares

Authors
  1. Nicolas Ferranti
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  2. Jairo Francisco de Souza
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  3. Stênio Sã Rosário Furtado Soares
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Correspondence to Jairo Francisco de Souza.

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Appendix

Appendix

Table 6 Fmeasure comparison
Full size table

This appendix shows the full tests table containing all test instances used in this work with its respective test number of the OAEI biblio benchmark. Table 7 shows the best value of f-measure found and its respective execution time for both optimization algorithms with the configuration described in Table 3.

Table 7 Full results of each test instance, best f-measure and respective time in seconds for the PPA-p20-g80 and GA-p150-g-150
Full size table

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Ferranti, N., de Souza, J.F. & Soares, S.S.R.F. A Prey–Predator Approach for Ontology Meta-matching. J Data Semant 10, 229–240 (2021). https://doi.org/10.1007/s13740-021-00125-y

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  • DOI: https://doi.org/10.1007/s13740-021-00125-y

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