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03312nam a22005295i 4500 |
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978-3-319-45654-6 |
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DE-He213 |
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20170202153118.0 |
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cr nn 008mamaa |
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170202s2017 gw | s |||| 0|eng d |
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|a 9783319456546
|9 978-3-319-45654-6
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|a 10.1007/978-3-319-45654-6
|2 doi
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|d GrThAP
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|a Q334-342
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|a TJ210.2-211.495
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|a UYQ
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|a TJFM1
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|a COM004000
|2 bisacsh
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|a 006.3
|2 23
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|a Exploiting Linked Data and Knowledge Graphs in Large Organisations
|h [electronic resource] /
|c edited by Jeff Z. Pan, Guido Vetere, Jose Manuel Gomez-Perez, Honghan Wu.
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1 |
|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2017.
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| 300 |
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|a XVIII, 266 p. 59 illus., 44 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a text file
|b PDF
|2 rda
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0 |
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|a Part I Knowledge Graph Foundations & Architecture -- Part II Constructing, Understanding and Consuming Knowledge Graphs -- Part III Industrial Applications and Successful Stories.
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| 520 |
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|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 |
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0 |
|a Computer science.
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| 650 |
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0 |
|a Management information systems.
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| 650 |
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0 |
|a Data mining.
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| 650 |
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0 |
|a Artificial intelligence.
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| 650 |
1 |
4 |
|a Computer Science.
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| 650 |
2 |
4 |
|a Artificial Intelligence (incl. Robotics).
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| 650 |
2 |
4 |
|a Data Mining and Knowledge Discovery.
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| 650 |
2 |
4 |
|a Information Systems Applications (incl. Internet).
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| 650 |
2 |
4 |
|a Business Information Systems.
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| 700 |
1 |
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|a Pan, Jeff Z.
|e editor.
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| 700 |
1 |
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|a Vetere, Guido.
|e editor.
|
| 700 |
1 |
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|a Gomez-Perez, Jose Manuel.
|e editor.
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| 700 |
1 |
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|a Wu, Honghan.
|e editor.
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
0 |
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|t Springer eBooks
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| 776 |
0 |
8 |
|i Printed edition:
|z 9783319456522
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| 856 |
4 |
0 |
|u http://dx.doi.org/10.1007/978-3-319-45654-6
|z Full Text via HEAL-Link
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| 912 |
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|a ZDB-2-SCS
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| 950 |
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|a Computer Science (Springer-11645)
|
