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.

Keywords

Computer scienceKnowledge graphArtificial intelligence

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Publication Info

Year
2021
Type
review
Volume
54
Issue
4
Pages
1-37
Citations
1200
Access
Closed

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Aidan Hogan, Eva Blomqvist, Michael Cochez et al. (2021). Knowledge Graphs. ACM Computing Surveys , 54 (4) , 1-37. https://doi.org/10.1145/3447772

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DOI
10.1145/3447772