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Knowledge Graphs

Abstract : In this paper 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 and query languages that are used for knowledge graphs. We discuss the roles of schema, identity, and context in knowledge graphs. We explain how knowledge can be represented and extracted using a combination of deductive and inductive techniques. We summarise methods for the creation, enrichment, quality assessment, refinement, and publication of knowledge graphs. We provide an overview of prominent open knowledge graphs and enterprise knowledge graphs, their applications, and how they use the aforementioned techniques. We conclude with high-level future research directions for knowledge graphs.
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Contributor : Florent Breuil Connect in order to contact the contributor
Submitted on : Wednesday, January 13, 2021 - 4:11:48 PM
Last modification on : Monday, August 8, 2022 - 5:00:06 PM

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  • HAL Id : emse-03109122, version 1
  • ARXIV : 2003.02320


Hogan Aidan, Eva Blomqvist, Michael Cochez, Claudia d'Amato, Gerard de Melo, et al.. Knowledge Graphs. [Technical Report] Mines Saint-Etienne. 2020. ⟨emse-03109122⟩



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