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Fuzzy Sets in Approximate Reasoning and Information Systems

  • Book
  • © 1999

Overview

Editors:
  1. James C. Bezdek

    1. University of West Florida, USA

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    You can also search for this editor in PubMed   Google Scholar

  2. Didier Dubois

    1. IRIT, CNRS & University of Toulouse III, France

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    You can also search for this editor in PubMed   Google Scholar

  3. Henri Prade

    1. IRIT, CNRS & University of Toulouse III, France

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Part of the book series: The Handbooks of Fuzzy Sets (FSHS, volume 5)

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Table of contents (9 chapters)

  1. Front Matter

    Pages i-xv
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  2. Introduction

    1. Introduction: Fuzzy Sets in Approximate Reasoning and Intelligent Information Systems Technology

      • Didier Dubois, Henri Prade, Jim Bezdek
      Pages 1-13

  3. Part I Reasoning

    1. Front Matter

      Pages 15-15
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    2. Fuzzy Sets and Possibility Theory in Approximate and Plausible Reasoning

      • Bernadette Bouchon-Meunier, Didier Dubois, Lluis Godo, Henri Prade
      Pages 15-190

    3. Weighted Inference Systems

      • Vilém. Novák
      Pages 191-241

    4. Closure Operators in Fuzzy Set Theory

      • Loredana Biacino, Giangiacomo Gerla
      Pages 243-278

  4. Part II Learning and Fusion

    1. Front Matter

      Pages 279-279
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    2. Learning Fuzzy Decision Rules

      • Bernadette Bouchon-Meunier, Christophe Marsala
      Pages 279-304

    3. Neuro-Fuzzy Methods in Fuzzy Rule Generation

      • Detlef Nauck, Rudolf Kruse
      Pages 305-334

    4. Merging Fuzzy Information

      • Didier Dubois, Henri Prade, Ronald Yager
      Pages 335-401

  5. Part III Fuzzy Information Systems

    1. Front Matter

      Pages 403-403
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    2. Fuzzy Databases

      • Patrick Bosc, Bill B. Buckles, Frederick E. Petry, Olivier Pivert
      Pages 403-468

    3. Fuzzy Set Techniques in Information Retrieval

      • Donald H. Kraft, Gloria Bordogna, Gabriella Pasi
      Pages 469-510
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Keywords

About this book

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.

Editors and Affiliations

  • University of West Florida, USA

    James C. Bezdek

  • IRIT, CNRS & University of Toulouse III, France

    Didier Dubois, Henri Prade

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