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Knowledge Graph Consolidation by Unifying Synonymous Relationships

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The Semantic Web – ISWC 2019 (ISWC 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11778))

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Abstract

Entity-centric information resources in the form of huge RDF knowledge graphs have become an important part of today’s information systems. But while the integration of independent sources promises rich information, their inherent heterogeneity also poses threats to the overall usefulness. To some degree challenges of heterogeneity have been addressed by creating underlying ontological structures. Yet, our analysis shows that synonymous relationships are still prevalent in current knowledge graphs. In this paper we compare state-of-the-art relational learning techniques to analyze the semantics of relationships for unifying synonymous relationships. By embedding relationships into latent feature models, we are able to identify relationships showing the same semantics in a data-driven fashion. The resulting relationship synonyms can be used for knowledge graph consolidation. We evaluate our technique on Wikidata, Freebase and DBpedia: we identify hundreds of existing relationship duplicates with very high precision, outperforming the current state-of-the-art method.

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Notes

  1. 1.

    http://oaei.ontologymatching.org/.

  2. 2.

    https://github.com/JanKalo/RelAlign.

  3. 3.

    https://github.com/JanKalo/RelAlign.

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Authors and Affiliations

  1. Institut für Informationssysteme, Technische Universität Braunschweig, Mühlenpfordtstraße 23, 38106, Brunswick, Germany

    Jan-Christoph Kalo, Philipp Ehler & Wolf-Tilo Balke

Authors
  1. Jan-Christoph Kalo
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  2. Philipp Ehler
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  3. Wolf-Tilo Balke
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Corresponding author

Correspondence to Jan-Christoph Kalo .

Editor information

Editors and Affiliations

  1. Fondazione Bruno Kessler, Trento, Italy

    Chiara Ghidini

  2. Linköping University, Linköping, Sweden

    Olaf Hartig

  3. University of Bonn, Bonn, Germany

    Maria Maleshkova

  4. University of Economics Prague, Prague, Czech Republic

    Vojtěch Svátek

  5. University of Illinois at Chicago, Chicago, IL, USA

    Isabel Cruz

  6. University of Chile, Santiago, Chile

    Aidan Hogan

  7. Memect Technology, Beijing, China

    Jie Song

  8. Mines Saint-Etienne, Saint-Etienne, France

    Maxime Lefrançois

  9. Inria Sophia Antipolis - Méditerranée, Sophia Antipolis, France

    Fabien Gandon

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Kalo, JC., Ehler, P., Balke, WT. (2019). Knowledge Graph Consolidation by Unifying Synonymous Relationships. In: Ghidini, C., et al. The Semantic Web – ISWC 2019. ISWC 2019. Lecture Notes in Computer Science(), vol 11778. Springer, Cham. https://doi.org/10.1007/978-3-030-30793-6_16

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  • DOI: https://doi.org/10.1007/978-3-030-30793-6_16

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-30793-6

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