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Knowledge Graphs

Hogan, Aidan (author)
DCC, Universidad de Chile; IMFD
Blomqvist, Eva, 1977- (author)
Linköpings universitet,Interaktiva och kognitiva system,Tekniska fakulteten
Cochez, Michael (author)
Vrije Universiteit Amsterdam and Discovery Lab, Elsevier
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d'Amato, Claudia (author)
University of Bari
Melo, Gerard de (author)
HPI, University of Potsdam and Rutgers University
Gutierrez, Claudio (author)
DCC, Universidad de Chile; IMFD
Kirrane, Sabrina (author)
WU Vienna
Gayo, José Emilio Labra (author)
Universidad de Oviedo
Navigli, Roberto (author)
Sapienza University of Rome
Neumaier, Sebastian (author)
St. Pölten University of Applied Sciences
Ngomo, Axel-Cyrille Ngonga (author)
DICE, Universität Paderborn
Polleres, Axel (author)
WU Vienna
Rashid, Sabbir M. (author)
Tetherless World Constellation
Rula, Anisa (author)
University of Brescia
Schmelzeisen, Lukas (author)
Universität Stuttgart
Sequeda, Juan (author)
data.world
Staab, Steffen (author)
Universität Stuttgart and University of Southampton
Zimmermann, Antoine (author)
École des mines de Saint-Étienne
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 (creator_code:org_t)
ISBN 9781636392356
Morgan & Claypool Publishers, 2021
English 257 s.
Series: Synthesis Lectures on Data, Semantics, and Knowledge, 2691-2023 2691-2031 ; Vol. 12, No. 2
  • Book (other academic/artistic)
Abstract Subject headings
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  • This 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.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
NATURVETENSKAP  -- Data- och informationsvetenskap -- Systemvetenskap, informationssystem och informatik (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences -- Information Systems (hsv//eng)

Keyword

Semantic Web

Publication and Content Type

vet (subject category)
bok (subject category)

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