Overview
- Provides an academic, yet practical perspective on knowledge engineering with rule-based systems
- Systematically presents the author’s research results in the area of intelligent rule-based systems
- Focuses on the semantic knowledge engineering (SKE) approach
- Is enriched with selected examples of intelligent system design
- Includes supplementary material: sn.pub/extras
Part of the book series: Intelligent Systems Reference Library (ISRL, volume 130)
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Table of contents (17 chapters)
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Front Matter
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Domain of Rule-Based Systems
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Front Matter
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Practical Studies in Semantic Knowledge Engineering
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Front Matter
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Keywords
About this book
This book proposes a consistent methodology for building intelligent systems.
It puts forward several formal models for designing and implementing rules-based systems, and presents illustrative case studies of their applications.
These include software engineering, business process systems, Semantic Web, and context-aware systems on mobile devices. Rules offer an intuitive yet powerful method for representing human knowledge, and intelligent systems based on rules have many important applications. However, their practical development requires proper techniques and models - a gap that this book effectively addresses.
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Modeling with Rules Using Semantic Knowledge Engineering
Authors: Grzegorz J. Nalepa
Series Title: Intelligent Systems Reference Library
DOI: https://doi.org/10.1007/978-3-319-66655-6
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing AG 2018
Hardcover ISBN: 978-3-319-66654-9Published: 14 October 2017
Softcover ISBN: 978-3-319-88294-9Published: 15 August 2018
eBook ISBN: 978-3-319-66655-6Published: 04 October 2017
Series ISSN: 1868-4394
Series E-ISSN: 1868-4408
Edition Number: 1
Number of Pages: XXVI, 435
Number of Illustrations: 95 b/w illustrations, 35 illustrations in colour
Topics: Computational Intelligence, Artificial Intelligence, Control and Systems Theory