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REGNUM: Generating Logical Rules with Numerical Predicates in Knowledge Graphs

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The Semantic Web (ESWC 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13870))

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Abstract

Mining logical rules from a knowledge graph (KG) can reveal useful patterns for predicting facts, curating the KG, and identifying trends. However, many rule mining systems face challenges when working with numerical data because numerical predicates can take a large number of values, leading to a huge search space. In this work, we present REGNUM, a system that addresses this issue by generating rules with numerical constraints. REGNUM extends the body of rules mined from a KG by using supervised discretization of numerical values with decision trees to increase the confidence of the rules without sacrificing significance. Our experimental results show that the numerical rules have a higher overall quality than the parent rules and are effective at making better predictions.

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Notes

  1. 1.

    Membership to a class, can also be represented with a binary predicate, i.e., type(X, Y).

  2. 2.

    Variables are represented using lowercase letters whereas capitalized letters denote constants.

  3. 3.

    https://www.stardog.com/.

  4. 4.

    https://github.com/armitakhn/REGNUM.

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Acknowledgements

This work has been supported by the project PSPC AIDA: 2019-PSPC-09 funded by BPI-France.

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Authors and Affiliations

  1. LISN, CNRS (UMR 9015), Paris Saclay University, 91405, Orsay, France

    Armita Khajeh Nassiri, Nathalie Pernelle & Fatiha Saïs

  2. LIPN, CNRS (UMR 7030), University Sorbonne Paris Nord, Paris, France

    Nathalie Pernelle

Authors
  1. Armita Khajeh Nassiri
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  2. Nathalie Pernelle
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  3. Fatiha Saïs
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Corresponding authors

Correspondence to Armita Khajeh Nassiri , Nathalie Pernelle or Fatiha Saïs .

Editor information

Editors and Affiliations

  1. Universidade de Lisboa, Lisbon, Portugal

    Catia Pesquita

  2. University of London, London, UK

    Ernesto Jimenez-Ruiz

  3. Rensselaer Polytechnic Institute, Troy, MI, USA

    Jamie McCusker

  4. Universidade de Lisboa, Lisbon, Portugal

    Daniel Faria

  5. Fondazione Bruno Kessler, Povo, Trento, Italy

    Mauro Dragoni

  6. KU Leuven, Sint-Katelijne-Waver, Belgium

    Anastasia Dimou

  7. EURECOM, Biot, France

    Raphael Troncy

  8. University of Mannheim, Mannheim, Germany

    Sven Hertling

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Khajeh Nassiri, A., Pernelle, N., Saïs, F. (2023). REGNUM: Generating Logical Rules with Numerical Predicates in Knowledge Graphs. In: Pesquita, C., et al. The Semantic Web. ESWC 2023. Lecture Notes in Computer Science, vol 13870. Springer, Cham. https://doi.org/10.1007/978-3-031-33455-9_9

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  • DOI: https://doi.org/10.1007/978-3-031-33455-9_9

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  • Online ISBN: 978-3-031-33455-9

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