Overview
- Addresses the topic of exploiting enterprise linked data with a focus on knowledge construction and accessibility within enterprises
- Focuses on the key technologies for constructing, understanding and employing knowledge graphs
- Written for academic researchers, knowledge engineers, and IT professionals who are interested in learning about experiences of using knowledge graphs in enterprises and large organisations
- Includes supplementary material: sn.pub/extras
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Table of contents (9 chapters)
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Front Matter
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Knowledge Graph Foundations & Architecture
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Front Matter
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Constructing, Understanding and Consuming Knowledge Graphs
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Front Matter
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Industrial Applications and Successful Stories
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Front Matter
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Back Matter
Keywords
About this book
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.
Reviews
“Internet corporations have proved the power that Knowledge Graph can bring to business. This book provides a thorough guide in this line for practisers, researchers and students.” (Junlan Feng, Director of Big Data Analytics Lab, China Mobile Research)
“Knowledge Graph help companies unify their view of the world in the form of shared schemas or ontologies for core entities in their business. It is the right time to implement the concepts clearly introduced in this book.” (Peter Mika, Director of Semantic Search, Yahoo Lab)
“Working with auditable knowledge is key for a next generation of enterprise conversational systems. This book gives a great picture of how to do that work.” (David Nahamoo, IBM Fellow, Speech CTO at IBM Research)
Editors and Affiliations
About the editors
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 Advanced Studies Italy. He has led/worked in many research and development projects in KR, NLP and ontology. He also leads Senso Comune (www.sensocomune.it), a collaborative initiative for building an open KB of the Italian language.
Jose Manuel Gomez-Perez is the Director R&D at Expert System Iberia (ESI). His expertise is on supporting users in creating, sharing, and accessing knowledge. He has a long experience in European R&D projects, privately-funded technology transfer activities and R&D projects.
Honghan Wu is a data scientist in NIHR Maudsley Biomedical Research Centre at King's College London. His current research focus is on annotating, analysing and searching large scale healthcare data by utilising Knowledge Graph techniques.
Bibliographic Information
Book Title: Exploiting Linked Data and Knowledge Graphs in Large Organisations
Editors: Jeff Z. Pan, Guido Vetere, Jose Manuel Gomez-Perez, Honghan Wu
DOI: https://doi.org/10.1007/978-3-319-45654-6
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing Switzerland 2017
Hardcover ISBN: 978-3-319-45652-2Published: 09 February 2017
Softcover ISBN: 978-3-319-83339-2Published: 13 July 2018
eBook ISBN: 978-3-319-45654-6Published: 24 January 2017
Edition Number: 1
Number of Pages: XVIII, 266
Number of Illustrations: 15 b/w illustrations, 44 illustrations in colour
Topics: Artificial Intelligence, Data Mining and Knowledge Discovery, Information Systems Applications (incl. Internet), Business Information Systems