Knowledge Graphs: Introduction, History and, Perspectives

Autor: Vinay K. Chaudhri, Chaitanya Baru, Naren Chittar, Xin Luna Dong, Michael Genesereth, James Hendler, Aditya Kalyanpur, Douglas B. Lenat, Juan Sequeda, Denny Vrandečić, Kuansan Wang
Rok vydání: 2022
Předmět:
Zdroj: AI Magazine; Vol. 43 No. 1: Spring 2022; 17-29
ISSN: 2371-9621
0738-4602
Popis: 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.
Databáze: OpenAIRE
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