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Exploiting linked data and knowledge...

Pan, Jeff Z.

Exploiting linked data and knowledge graphs in large organisations

Record Type:	Electronic resources : Monograph/item
Title/Author:	Exploiting linked data and knowledge graphs in large organisationsedited by Jeff Z. Pan ... [et al.].
other author:	Pan, Jeff Z.
Published:	Cham :Springer International Publishing :2017.
Description:	xviii, 266 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Knowledge representation (Information theory)
Online resource:	http://dx.doi.org/10.1007/978-3-319-45654-6
ISBN:	9783319456546$q(electronic bk.)

Exploiting linked data and knowledge graphs in large organisations
Exploiting linked data and knowledge graphs in large organisations[electronic resource] /edited by Jeff Z. Pan ... [et al.]. - Cham :Springer International Publishing :2017. - xviii, 266 p. :ill., digital ;24 cm.

Part I Knowledge Graph Foundations & Architecture -- Part II Constructing, Understanding and Consuming Knowledge Graphs -- Part III Industrial Applications and Successful Stories.

This book addresses the topic of exploiting enterprise-linked data with a particular focus on knowledge construction and accessibility within enterprises. It identifies the gaps between the requirements of enterprise knowledge consumption and "standard" data consuming technologies by analysing real-world use cases, and proposes the enterprise knowledge graph to fill such gaps. It provides concrete guidelines for effectively deploying linked-data graphs within and across business organizations. It is divided into three parts, focusing on the key technologies for constructing, understanding and employing knowledge graphs. Part 1 introduces basic background information and technologies, and presents a simple architecture to elucidate the main phases and tasks required during the lifecycle of knowledge graphs. Part 2 focuses on technical aspects; it starts with state-of-the art knowledge-graph construction approaches, and then discusses exploration and exploitation techniques as well as advanced question-answering topics concerning knowledge graphs. Lastly, Part 3 demonstrates examples of successful knowledge graph applications in the media industry, healthcare and cultural heritage, and offers conclusions and future visions.

ISBN: 9783319456546$q(electronic bk.)

Standard No.: 10.1007/978-3-319-45654-6doiSubjects--Topical Terms:

226484
Knowledge representation (Information theory)

LC Class. No.: Q387 / .E97 2017

Dewey Class. No.: 006.332

Exploiting linked data and knowledge graphs in large organisations
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505 0 $a Part I Knowledge Graph Foundations & Architecture -- Part II Constructing, Understanding and Consuming Knowledge Graphs -- Part III Industrial Applications and Successful Stories.
520 $a This book addresses the topic of exploiting enterprise-linked data with a particular focus on knowledge construction and accessibility within enterprises. It identifies the gaps between the requirements of enterprise knowledge consumption and "standard" data consuming technologies by analysing real-world use cases, and proposes the enterprise knowledge graph to fill such gaps. It provides concrete guidelines for effectively deploying linked-data graphs within and across business organizations. It is divided into three parts, focusing on the key technologies for constructing, understanding and employing knowledge graphs. Part 1 introduces basic background information and technologies, and presents a simple architecture to elucidate the main phases and tasks required during the lifecycle of knowledge graphs. Part 2 focuses on technical aspects; it starts with state-of-the art knowledge-graph construction approaches, and then discusses exploration and exploitation techniques as well as advanced question-answering topics concerning knowledge graphs. Lastly, Part 3 demonstrates examples of successful knowledge graph applications in the media industry, healthcare and cultural heritage, and offers conclusions and future visions.
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650 0 $a Linked data. $3 683691
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650 2 4 $a Data Mining and Knowledge Discovery. $3 275288
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