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Industry-scale Knowledge Graphs: Lessons and Challenges

Yuqing Gao
Anshu Jain
Anant Narayanan
Alan Patterson
Jamie Taylor
Communications of the ACM, vol. 62 (8) (2019), pp. 36-43


Knowledge graphs are critical to many enterprises today: they provide the structured data and factual knowledge that drives many products and makes them more intelligent and "magical." In this paper, we bring together the experience of building and using knowledge graphs in five diverse companies to compare similarities and differences and to discuss challenges that all knowledge-driven enterprises face today: The Bing knowledge graph at Microsoft and the Google knowledge graph support search and answering questions in search and during conversations. Facebook has the world's largest social graph, and also starts to include information that Facebook users care about, such as information about music, movies, celebrities, and places. The eBay knowledge graph describes the enormous variety of products and their connections. Finally, the Knowledge Graph Framework for IBM’s Watson Discovery Offerings provides an offering that allows others to build their own knowledge graph against a pre-built components. We discuss the diverse requirements of these knowledge graphs and many common challenges in building knowledge graphs at this scale. This article summarizes and expands on the panel discussion that the authors conducted at the International Semantic Web Conference in Asilomar, California in October 2018.