Rule Induction and Reasoning over Knowledge Graphs

  • Daria StepanovaEmail author
  • Mohamed H. Gad-Elrab
  • Vinh Thinh Ho
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11078)


Advances in information extraction have enabled the automatic construction of large knowledge graphs (KGs) like DBpedia, Freebase, YAGO and Wikidata. Learning rules from KGs is a crucial task for KG completion, cleaning and curation. This tutorial presents state-of-the-art rule induction methods, recent advances, research opportunities as well as open challenges along this avenue. We put a particular emphasis on the problems of learning exception-enriched rules from highly biased and incomplete data. Finally, we discuss possible extensions of classical rule induction techniques to account for unstructured resources (e.g., text) along with the structured ones.


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Authors and Affiliations

  • Daria Stepanova
    • 1
    Email author
  • Mohamed H. Gad-Elrab
    • 1
  • Vinh Thinh Ho
    • 1
  1. 1.Max Planck Institute for InformaticsSaarbrückenGermany

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