Principles of Semantic Networks: Explorations in the Representation of Knowledge

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John F. Sowa
Morgan Kaufmann, Jul 10, 2014 - Computers - 594 pages
Principles of Semantic Networks: Explorations in the Representation of Knowledge provides information pertinent to the theory and applications of semantic networks. This book deals with issues in knowledge representation, which discusses theoretical topics independent of particular implementations. Organized into three parts encompassing 19 chapters, this book begins with an overview of semantic network structure for representing knowledge as a pattern of interconnected nodes and arcs. This text then analyzes the concepts of subsumption and taxonomy and synthesizes a framework that integrates many previous approaches and goes beyond them to provide an account of abstract and partially defines concepts. Other chapters consider formal analyses, which treat the methods of reasoning with semantic networks and their computational complexity. This book discusses as well encoding linguistic knowledge. The final chapter deals with a formal approach to knowledge representation that builds on ideas originating outside the artificial intelligence literature in research on foundations for programming languages. This book is a valuable resource for mathematicians.
 

Contents

ISSUES IN KNOWLEDGE REPRESENTATION
1
FORMAL ANALYSES
229
SYSTEMS FOR KNOWLEDGE REPRESENTATION
381

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About the author (2014)

John Sowa is a Fellow of the American Association for Artificial Intelligence. He earned a bachelor s degree in Mathematics from MIT, a master s degree in Applied Mathematics from Harvard, and a doctorate in Computer Science from the Vrije Universiteit Brussel. He has published and edited several books and dozens of articles on artificial intelligence and related topics.

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