Exploiting Linked Data and Knowledge Graphs in Large Organisations [electronic resource] / / edited by Jeff Z. Pan, Guido Vetere, Jose Manuel Gomez-Perez, Honghan Wu.. — 1st ed. 2017.. — XVIII, 266 p. 59 illus., 44 illus. in color. : online resource.
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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Анотація: 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.
9783319456546
10.1007/978-3-319-45654-6 doi
Artificial intelligence. Data mining. Application software. Management information systems. Artificial Intelligence. Data Mining and Knowledge Discovery. Information Systems Applications (incl. Internet). Business Information Systems.