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Knowledge-Based Matching of n-ary Tuples

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Book cover Ontologies and Concepts in Mind and Machine (ICCS 2020)

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Abstract

An increasing number of data and knowledge sources are accessible by human and software agents in the expanding Semantic Web. Sources may differ in granularity or completeness, and thus be complementary. Consequently, they should be reconciled in order to unlock the full potential of their conjoint knowledge. In particular, units should be matched within and across sources, and their level of relatedness should be classified into equivalent, more specific, or similar. This task is challenging since knowledge units can be heterogeneously represented in sources (e.g., in terms of vocabularies). In this paper, we focus on matching n-ary tuples in a knowledge base with a rule-based methodology. To alleviate heterogeneity issues, we rely on domain knowledge expressed by ontologies. We tested our method on the biomedical domain of pharmacogenomics by searching alignments among 50,435 n-ary tuples from four different real-world sources. Results highlight noteworthy agreements and particularities within and across sources.

Supported by the PractiKPharma project, founded by the French National Research Agency (ANR) under Grant ANR15-CE23-0028, by the IDEX “Lorraine Université d’Excellence” (15-IDEX-0004), and by the Snowball Inria Associate Team.

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Notes

  1. 1.

    See Appendix B and Appendix C for the proof and examples.

  2. 2.

    See Appendix D for a detailed example.

  3. 3.

    \(D \sqsubset C\) means that \(D \sqsubseteq C\) and \(D \not \equiv C\).

  4. 4.

    See Appendix E and Appendix F for the proof and examples.

  5. 5.

    https://pgxlod.loria.fr.

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Authors and Affiliations

  1. Université de Lorraine, CNRS, Inria, LORIA, 54000, Nancy, France

    Pierre Monnin, Miguel Couceiro, Amedeo Napoli & Adrien Coulet

Authors
  1. Pierre Monnin
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  2. Miguel Couceiro
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  3. Amedeo Napoli
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  4. Adrien Coulet
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Corresponding author

Correspondence to Pierre Monnin .

Editor information

Editors and Affiliations

  1. FIZ Karlsruhe – Leibniz Institute for Information Infrastructure, Karlsruhe, Germany

    Mehwish Alam

  2. Institute of Information Systems, University of Lübeck, Lübeck, Germany

    Tanya Braun

  3. Department of Computing Science, University of Aberdeen, Aberdeen, UK

    Bruno Yun

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Monnin, P., Couceiro, M., Napoli, A., Coulet, A. (2020). Knowledge-Based Matching of n-ary Tuples. In: Alam, M., Braun, T., Yun, B. (eds) Ontologies and Concepts in Mind and Machine. ICCS 2020. Lecture Notes in Computer Science(), vol 12277. Springer, Cham. https://doi.org/10.1007/978-3-030-57855-8_4

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  • DOI: https://doi.org/10.1007/978-3-030-57855-8_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-57854-1

  • Online ISBN: 978-3-030-57855-8

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