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Exploiting Linked Data and Knowledge Graphs in Large Organisations
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Description for Exploiting Linked Data and Knowledge Graphs in Large Organisations
Hardcover. Editor(s): Pan, Jeff Z. Num Pages: 266 pages, 15 black & white illustrations, 44 colour illustrations, 38 colour tables, biography. BIC Classification: KJQ; UNF; UNH; UYF. Category: (P) Professional & Vocational. Dimension: 244 x 163 x 23. Weight in Grams: 584.
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 ... Read more
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 ... Read more
Product Details
Format
Hardback
Publication date
2017
Publisher
Springer
Condition
New
Number of Pages
266
Place of Publication
Cham, Switzerland
ISBN
9783319456522
SKU
V9783319456522
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About N/A
About the Editors: Jeff Z. Pan is a Reader (Professor) at University of Aberdeen. He is the Chief Scientist of the EC Marie Curie K-Drive project and has edited many books/proceedings on Semantic Technologies and Linked Data. He is well known for his work on knowledge construction, reasoning and exploitation. Guido Vetere leads the IBM Center for ... Read more
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