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Knowledge Graphs: Introduction, History and, Perspectives

Where it appeared

Published inAI Magazine
PublisherAssociation for the Advancement of Artificial Intelligence
Volume43
Issue1
Pages17--29

Identifiers

DOI10.1002/aaai.12033
OpenAlexW4229377239

From OpenAlex, which stores abstracts as an index of words and their positions: what is shown is rebuilt from that, and reads fluently whether or not it is what the author wrote.

Abstract

Abstract Knowledge graphs (KGs) have emerged as a compelling abstraction for organizing the world's structured knowledge and for integrating information extracted from multiple data sources. They are also beginning to play a central role in representing information extracted by AI systems, and for improving the predictions of AI systems by giving them knowledge expressed in KGs as input. The goals of this article are to (a) introduce KGs and discuss important areas of application that have gained recent prominence; (b) situate KGs in the context of the prior work in AI; and (c) present a few contrasting perspectives that help in better understanding KGs in relation to related technologies.

How it got here

How it got hereagent via openalex
Added2026-10-23 13:37 UTC
Not denied bya person 2026-10-29 17:12 UTC

Cite it as

@article{chaudhri2022knowledge,
  title        = {Knowledge Graphs: Introduction, History and, Perspectives},
  author       = {Vinay K. Chaudhri and Chaitanya K. Baru and Naren Chittar and Dong Xin and Michael Genesereth and James Hendler and Aditya A. Kalyanpur and Douglas B. Lenat and Juan Sequeda and Denny Vrandečić and Kuansan Wang},
  year         = {2022},
  journal      = {AI Magazine},
  publisher    = {Association for the Advancement of Artificial Intelligence},
  volume       = {43},
  number       = {1},
  pages        = {17--29},
  doi          = {10.1002/aaai.12033},
}

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