9783319456522-3319456520-Exploiting Linked Data and Knowledge Graphs in Large Organisations

Exploiting Linked Data and Knowledge Graphs in Large Organisations

ISBN-13: 9783319456522
ISBN-10: 3319456520
Edition: 1st ed. 2017
Author: Pan
Publication date: 2017
Publisher: Springer
Format: Hardcover 284 pages
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Book details

ISBN-13: 9783319456522
ISBN-10: 3319456520
Edition: 1st ed. 2017
Author: Pan
Publication date: 2017
Publisher: Springer
Format: Hardcover 284 pages

Summary

Exploiting Linked Data and Knowledge Graphs in Large Organisations (ISBN-13: 9783319456522 and ISBN-10: 3319456520), written by authors Pan, was published by Springer in 2017. With an overall rating of 3.6 stars, it's a notable title among other AI & Machine Learning (Computer Science) books. You can easily purchase or rent Exploiting Linked Data and Knowledge Graphs in Large Organisations (Hardcover) from BooksRun, along with many other new and used AI & Machine Learning books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

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.

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