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TitleFuzzy Sets in Approximate Reasoning and Information Systems [electronic resource] / edited by James C. Bezdek, Didier Dubois, Henri Prade
ImprintBoston, MA : Springer US : Imprint: Springer, 1999
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Descript XV, 514 p. online resource


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


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

Mathematics Data structures (Computer science) Artificial intelligence Management information systems Computer science Mathematical logic Mathematics Mathematical Logic and Foundations Artificial Intelligence (incl. Robotics) Management of Computing and Information Systems Data Structures Cryptology and Information Theory


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