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020 _a9783031019180
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024 7 _a10.1007/978-3-031-01918-0
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072 7 _aCOM060160
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082 0 4 _a006.76
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100 1 _aHogan, Aidan.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_980443
245 1 0 _aKnowledge Graphs
_h[electronic resource] /
_cby Aidan Hogan, Eva Blomqvist, Michael Cochez, Claudia d'Amato, Gerard de Melo, Claudio Gutierrez, Sabrina Kirrane, Jose Emilio Labra Gayo, Roberto Navigli, Sebastian Neumaier, Axel Polleres, Sabbir Rashid, Anisa Rula, Antoine Zimmermann, Lukas Schmelzeisen, Axel-Cyrille Ngonga Ngomo, Juan Sequeda, Steffen Staab.
250 _a1st ed. 2022.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2022.
300 _aXIX, 237 p. 2 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
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490 1 _aSynthesis Lectures on Data, Semantics, and Knowledge,
_x2691-2031
505 0 _aPreface -- Acknowledgments -- Introduction -- Data Graphs -- Schema, Identity, and Context -- Deductive Knowledge -- Inductive Knowledge -- Creation and Enrichment -- Quality Assessment -- Refinement -- Publication -- Knowledge Graphs in Practice -- Conclusions -- Bibliography -- Authors' Biographies.
520 _aThis 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.
650 0 _aInternet programming.
_935503
650 0 _aOntology.
_95277
650 1 4 _aWeb Development.
_935505
650 2 4 _aOntology.
_95277
700 1 _aBlomqvist, Eva.
_eauthor.
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_4http://id.loc.gov/vocabulary/relators/aut
_980444
700 1 _aCochez, Michael.
_eauthor.
_4aut
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_980445
700 1 _ad'Amato, Claudia.
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_980446
700 1 _aMelo, Gerard de.
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_980447
700 1 _aGutierrez, Claudio.
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_980448
700 1 _aKirrane, Sabrina.
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_980449
700 1 _aLabra Gayo, Jose Emilio.
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_980450
700 1 _aNavigli, Roberto.
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_980451
700 1 _aNeumaier, Sebastian.
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_4aut
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_980452
700 1 _aPolleres, Axel.
_eauthor.
_4aut
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_980453
700 1 _aRashid, Sabbir.
_eauthor.
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_980454
700 1 _aRula, Anisa.
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_980455
700 1 _aZimmermann, Antoine.
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_980456
700 1 _aSchmelzeisen, Lukas.
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_980457
700 1 _aNgonga Ngomo, Axel-Cyrille.
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_980458
700 1 _aSequeda, Juan.
_eauthor.
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_980459
700 1 _aStaab, Steffen.
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_980460
710 2 _aSpringerLink (Online service)
_980461
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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830 0 _aSynthesis Lectures on Data, Semantics, and Knowledge,
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856 4 0 _uhttps://doi.org/10.1007/978-3-031-01918-0
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