Knowledge Graphs

Aidan Hogan, Eva Blomqvist, Michael Cochez, Gerard de Melo, Claudio Gutierrez, Sabrina Kirrane, José Emilio Labra Gayo, Roberto Navigli, Sebastian Neumaier, Axel-Cyrille Ngonga Ngomo, Axel Polleres, Sabbir M. Rashid, Anisa Rula, Lukas Schmelzeisen, Juan Sequeda, Steffen Staab, Antoine Zimmermann

Publication: Scientific journalJournal articleResearchpeer-review

Abstract

In this article, we provide a comprehensive introduction to knowledge graphs, which have recently garnered significant attention from both industry and academia in scenarios that require exploiting diverse, dynamic, large-scale collections of data. After some opening remarks, we motivate and contrast various graph-based data models, as well as languages used to query and validate knowledge graphs. We explain how knowledge can be represented and extracted using a combination of deductive and inductive techniques. We conclude with high-level future research directions for knowledge graphs.
Original languageEnglish
Pages (from-to)1 - 37
JournalACM Computing Surveys
Volume54
DOIs
Publication statusPublished - 2021

Austrian Classification of Fields of Science and Technology (ÖFOS)

  • 102 not use (legacy)
  • 102001 Artificial intelligence
  • 102015 Information systems
  • 502050 Business informatics
  • 505002 Data protection

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