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dc.contributor.authorHogan, Aidan
dc.contributor.authorGutierrez, Claudio
dc.contributor.authorCochcz, Michael
dc.contributor.authorde Melo, Gerard
dc.contributor.authorKirranc, Sabrina
dc.contributor.authorPollcrcs, Axel
dc.contributor.authorNavigli, Roberto
dc.contributor.authorNgonga Ngomo, Axcl-Cyrille
dc.contributor.authorRashid, Sabbir
dc.contributor.authorSchmclzciscn, Lukas
dc.contributor.authorStaab, Stefan
dc.contributor.authorBlomqvist, Eva
dc.contributor.authord’Amato, Claudia
dc.contributor.authorGayo, José Emilio Labra
dc.contributor.authorNcumaicr, Sebastian
dc.identifier.citationAidan Hogan, Claudio Gutierrez, Michael Cochcz, Gerard de Melo, Sabrina Kirranc, Axel Pollcrcs, Roberto Navigli, Axcl-Cyrille Ngonga Ngomo, Sabbir M. Rashid, Lukas Schmclzciscn, Steffen Staab, Eva Blomqvist, Claudia d’Amato, José Emilio Labra Gayo, Sebastian Ncumaicr, Anisa Rula, Juan Scqucda, Antoine Zimmermann. (2021). Knowledge graphs. Synthesis Lectures on Data, Semantics, and Knowledge, 12(2), 1-257. DOI: 10.2200/S01125ED1V01Y202109DSK022. September 2021en_US
dc.description.abstractThis book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying a graph-based abstraction to data, and are now broadly deployed in scenarios that require integrating and extracting value from multiple, diverse sources of data at large scale. The book defines knowledge graphs and provides a high-level overview of how they are used. It presents and contrasts popular graph models that are commonly used to represent data as graphs, and the languages by which they can be queried before describing how the resulting data graph can be enhanced with notions of schema, identity, and context. The book discusses how ontologies and rules can be used to encode knowledge as well as how inductive techniques—based on statistics, graph analytics, machine learning, etc.—can be used to encode and extract knowledge. It covers techniques for the creation, enrichment, assessment, and refinement of knowledge graphs and surveys recent open and enterprise knowledge graphs and the industries or applications within which they have been most widely adopted. The book closes by discussing the current limitations and future directions along which knowledge graphs are likely to evolve. This book is aimed at students, researchers, and practitioners who wish to learn more about knowledge graphs and how they facilitate extracting value from diverse data at large scale. To make the book accessible for newcomers, running examples and graphical notation are used throughout. Formal definitions and extensive references are also provided for those who opt to delve more deeply into specific topics.en_US
dc.publisherSpringer, Chamen_US
dc.relation.ispartofseriesSynthesis Lectures on Data, Semantics, and Knowledge;
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.titleKnowledge Graphsen_US

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Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States