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Machine Learning with and for Semantic Web Knowledge Graphs

  • Heiko PaulheimEmail author
Chapter
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11078)

Abstract

Large-scale cross-domain knowledge graphs, such as DBpedia or Wikidata, are some of the most popular and widely used datasets of the Semantic Web. In this paper, we introduce some of the most popular knowledge graphs on the Semantic Web. We discuss how machine learning is used to improve those knowledge graphs, and how they can be exploited as background knowledge in popular machine learning tasks, such as recommender systems.

Keywords

Knowledge graphs Semantic web Machine learning Background knowledge 

Notes

Acknowledgements

I would like to thank (in alphabetical order) Aldo Gangemi, André Melo, Christian Bizer, Daniel Ringler, Eneldo Loza Mencía, Heiner Stuckenschmidt, Jessica Rosati, Johanna Völker, Julian Seitner, Kai Eckert, Michael Cochez, Nicolas Heist, Petar Ristoski, Renato De Leone, Robert Meusel, Simone Paolo Ponzetto, Stefano Faralli, Sven Hertling, and Tommaso Di Noia for their valuable input to this paper.

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Authors and Affiliations

  1. 1.Data and Web Science GroupUniversity of MannheimMannheimGermany

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