@article{Chaudhri_Baru_Chittar_Dong_Genesereth_Hendler_Kalyanpur_Lenat_Sequeda_Vrandečić_Wang_2022, title={Knowledge Graphs: Introduction, History and, Perspectives }, volume={43}, url={https://ojs.aaai.org/aimagazine/index.php/aimagazine/article/view/19119}, DOI={10.1002/aaai.12033}, abstractNote={<p>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.</p>}, number={1}, journal={AI Magazine}, author={Chaudhri, Vinay and Baru, Chaitanya and Chittar, Naren and Dong , Xin and Genesereth, Michael and Hendler, James and Kalyanpur, Aditya and Lenat, Douglas and Sequeda, Juan and Vrandečić, Denny and Wang, Kuansan}, year={2022}, month={Mar.}, pages={17-29} }