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International Conference on Conceptual Structures

ICCS 2020: Ontologies and Concepts in Mind and Machine pp 18–32Cite as

Using Grammar-Based Genetic Programming for Mining Disjointness Axioms Involving Complex Class Expressions

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12277))

Abstract

In the context of the Semantic Web, learning implicit knowledge in terms of axioms from Linked Open Data has been the object of much current research. In this paper, we propose a method based on grammar-based genetic programming to automatically discover disjointness axioms between concepts from the Web of Data. A training-testing model is also implemented to overcome the lack of benchmarks and comparable research. The acquisition of axioms is performed on a small sample of DBpedia with the help of a Grammatical Evolution algorithm. The accuracy evaluation of mined axioms is carried out on the whole DBpedia. Experimental results show that the proposed method gives high accuracy in mining class disjointness axioms involving complex expressions.

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Notes

  1. 1.

    https://www.w3.org/TR/owl2-syntax/#Disjoint_Classes.

  2. 2.

    Available for download at http://bit.ly/2OtFqHp.

  3. 3.

    https://virtuoso.openlinksw.com/.

  4. 4.

    http://bit.ly/32YEQH1.

  5. 5.

    https://wiki.dbpedia.org/.

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Acknowledgments

This work has been supported by the French government, through the 3IA Côte d’Azur “Investments in the Future” project managed by the National Research Agency (ANR) with the reference number ANR-19-P3IA-0002.

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Authors and Affiliations

  1. Université Côte d’Azur, CNRS, Inria, I3S, Nice, France

    Thu Huong Nguyen & Andrea G. B. Tettamanzi

Authors
  1. Thu Huong Nguyen
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  2. Andrea G. B. Tettamanzi
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Corresponding author

Correspondence to Thu Huong Nguyen .

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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Nguyen, T.H., Tettamanzi, A.G.B. (2020). Using Grammar-Based Genetic Programming for Mining Disjointness Axioms Involving Complex Class Expressions. 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_2

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  • DOI: https://doi.org/10.1007/978-3-030-57855-8_2

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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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