β Scribed by Jeff Z. Pan, Guido Vetere, Jose Manuel Gomez-Perez, Honghan Wu (eds.)
No coin nor oath required. For personal study only.
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 βstandardβ
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 withinand 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.
Front Matter....Pages i-xviii
Enterprise Knowledge Graph: An Introduction....Pages 1-14
Front Matter....Pages 15-16
Knowledge Graph Foundations....Pages 17-55
Knowledge Architecture for Organisations....Pages 57-84
Front Matter....Pages 85-86
Construction of Enterprise Knowledge Graphs (I)....Pages 87-116
Construction of Enterprise Knowledge Graphs (II)*....Pages 117-146
Understanding Knowledge Graphs....Pages 147-180
Question Answering and Knowledge Graphs....Pages 181-212
Front Matter....Pages 213-214
Success Stories....Pages 215-236
Enterprise Knowledge Graph: Looking into the Future....Pages 237-249
Back Matter....Pages 251-266
Artificial Intelligence (incl. Robotics);Data Mining and Knowledge Discovery;Information Systems Applications (incl. Internet);Business Information Systems
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