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Article

REGNUM: Generating Logical Rules with Numerical Predicates in Knowledge Graphs

Authors:

Armita Khajeh Nassiri,

Nathalie Pernelle,

Fatiha SaïsAuthors Info & Claims

The Semantic Web: 20th International Conference, ESWC 2023, Hersonissos, Crete, Greece, May 28–June 1, 2023, Proceedings

Pages 139 - 155

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

Published: 28 May 2023 Publication History

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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Cited By

Purohit DChudasama YRivas AVidal M(2023)SPaRKLE : Symbolic caPtuRing of knowledge for Knowledge graph enrichment with LEarningProceedings of the 12th Knowledge Capture Conference 202310.1145/3587259.3627547(44-52)Online publication date: 5-Dec-2023
https://dl.acm.org/doi/10.1145/3587259.3627547

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Information & Contributors

Information

Published In

cover image Guide Proceedings

The Semantic Web: 20th International Conference, ESWC 2023, Hersonissos, Crete, Greece, May 28–June 1, 2023, Proceedings

May 2023

741 pages

ISBN:978-3-031-33454-2

DOI:10.1007/978-3-031-33455-9

Editors:
Catia Pesquita
Universidade de Lisboa, Lisbon, Portugal
,
Ernesto Jimenez-Ruiz
University of London, London, UK
,
Jamie McCusker
Rensselaer Polytechnic Institute, Troy, MI, USA
,
Daniel Faria
Universidade de Lisboa, Lisbon, Portugal
,
Mauro Dragoni
Fondazione Bruno Kessler, Povo, Trento, Italy
,
Anastasia Dimou
KU Leuven, Sint-Katelijne-Waver, Belgium
,
Raphael Troncy
EURECOM, Biot, France
,
Sven Hertling
University of Mannheim, Mannheim, Germany

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 28 May 2023

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Cited By

Purohit DChudasama YRivas AVidal M(2023)SPaRKLE : Symbolic caPtuRing of knowledge for Knowledge graph enrichment with LEarningProceedings of the 12th Knowledge Capture Conference 202310.1145/3587259.3627547(44-52)Online publication date: 5-Dec-2023
https://dl.acm.org/doi/10.1145/3587259.3627547

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