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Fuzzy Logic Framework for Ontology Instance Alignment

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Computational Science – ICCS 2022 (ICCS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13351))

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Abstract

The widely addressed topic of ontology alignment to this day contains several open research questions that remain either unanswered or only vaguely tackled. One of them is designating alignments of concept instances, which according to the literature are addressed in a handful of publications. Therefore, in this paper we propose a formal framework based on fuzzy logic that can be used to determine such mappings. We provide several similarity functions and a set of inference rules for combining them. The approach has been experimentally verified using widely accepted datasets provided by the Ontology Alignment Evaluation Initiative, yielding promising results.

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Authors and Affiliations

  1. Faculty of Information and Communication Technology, Wroclaw University of Science and Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

    Bogumiła Hnatkowska, Adrianna Kozierkiewicz & Marcin Pietranik

Authors
  1. Bogumiła Hnatkowska
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  2. Adrianna Kozierkiewicz
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  3. Marcin Pietranik
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Corresponding author

Correspondence to Adrianna Kozierkiewicz .

Editor information

Editors and Affiliations

  1. Brunel University London, London, UK

    Derek Groen

  2. University of Amsterdam, Amsterdam, The Netherlands

    Clélia de Mulatier

  3. AGH University of Science and Technology, Krakow, Poland

    Maciej Paszynski

  4. University of Amsterdam, Amsterdam, The Netherlands

    Valeria V. Krzhizhanovskaya

  5. University of Tennessee at Knoxville, Knoxville, TN, USA

    Jack J. Dongarra

  6. University of Amsterdam, Amsterdam, The Netherlands

    Peter M. A. Sloot

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Hnatkowska, B., Kozierkiewicz, A., Pietranik, M. (2022). Fuzzy Logic Framework for Ontology Instance Alignment. In: Groen, D., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2022. ICCS 2022. Lecture Notes in Computer Science, vol 13351. Springer, Cham. https://doi.org/10.1007/978-3-031-08754-7_68

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  • DOI: https://doi.org/10.1007/978-3-031-08754-7_68

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-08753-0

  • Online ISBN: 978-3-031-08754-7

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