Fuzzy Sets in Approximate Reasoning and Information Systems / Edition 1

by J.C. Bezdek, Didier Dubois, Henri Prade

Overview

Approximate reasoning is a key motivation in fuzzy sets and possibility theory. This volume provides a coherent view of this field, and its impact on database research and information retrieval. First, the semantic foundations of approximate reasoning are presented. Special emphasis is given to the representation of fuzzy rules and specialized types of approximate reasoning. Then syntactic aspects of approximate reasoning are surveyed and the algebraic underpinnings of fuzzy consequence relations are presented and explained. The second part of the book is devoted to inductive and neuro-fuzzy methods for learning fuzzy rules. It also contains new material on the application of possibility theory to data fusion. The last part of the book surveys the growing literature on fuzzy information systems. Each chapter contains extensive bibliographical material.
Fuzzy Sets in Approximate Reasoning and Information Systems is a major source of information for research scholars and graduate students in computer science and artificial intelligence, interested in human information processing.

Product Details

ISBN-13:	9780792385844
Publisher:	Springer US
Publication date:	07/31/1999
Series:	The Handbooks of Fuzzy Sets , #5
Edition description:	1999
Pages:	514
Product dimensions:	6.10(w) x 9.25(h) x 0.36(d)

Table of Contents

1 Fuzzy Sets and Possibility Theory in Approximate and Plausible Reasoning.- 2 Weighted Inference Systems.- 3 Closure Operators in Fuzzy set Theory.- 4 Learning Fuzzy Decision Rules.- 5 Neuro-Fuzzy Methods in Fuzzy Rule Generation.- 6 Merging Fuzzy Information.- 7 Fuzzy Databases.- 8 Fuzzy Set Techniques in Information Retrieval.

Editorial Reviews

Continuing the series of references for people engaged with fuzzy sets from graduate students to senior researchers, computer scientists and mathematicians set out the currently available concepts and methods from fuzzy set and possibility theory in the fields of knowledge representation, automated reasoning, knowledge-based systems, learning, data fusion, and information systems. Among the topics are approximate and plausible reasoning, weighted inference systems, learning fuzzy decision rules, merging fuzzy information, fuzzy databases, and fuzzy set techniques in information retrieval. Annotation c. Book News, Inc., Portland, OR (booknews.com)

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