Exploiting Linked Data and Knowledge Graphs in Large Organisations (Paperback, Softcover reprint of the original 1st ed. 2017)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Release date:	July 2018
First published:	2017
Editors:	Jeff Z. Pan • Guido Vetere • Jose Manuel Gomez- Perez • Honghan Wu
Dimensions:	235 x 155 x 15mm (L x W x T)
Format:	Paperback
Pages:	266
Edition:	Softcover reprint of the original 1st ed. 2017
ISBN-13:	978-3-319-83339-2
Categories:	Books > Business & Economics > Business & management > Business mathematics & systems > General Books > Computing & IT > Applications of computing > Databases > Data mining Books > Computing & IT > Applications of computing > Artificial intelligence > General Promotions
LSN:	3-319-83339-1
Barcode:	9783319833392

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