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Rough Set Theory and Granular Computing

  • Book
  • © 2003

Overview

Editors:
  1. Masahiro Inuiguchi

    1. Graduate School of Engineering, Osaka University, Osaka, Japan

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    You can also search for this editor in PubMed   Google Scholar

  2. Shoji Hirano

    1. Shimane Medical University, Izumo, Shimane-ken, Japan

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    You can also search for this editor in PubMed   Google Scholar

  3. Shusaku Tsumoto

    1. Shimane Medical University, Izumo, Shimane-ken, Japan

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  • Recent research and applications in rough set theory and granular computing
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Fuzziness and Soft Computing (STUDFUZZ, volume 125)

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Table of contents (28 chapters)

  1. Front Matter

    Pages I-XV
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  2. Bayes’ Theorem — the Rough Set Perspective

    1. Bayes’ Theorem — the Rough Set Perspective

      • Zdzislaw Pawlak
      Pages 1-12

  3. Approximation Spaces in Rough Neurocomputing

    1. Approximation Spaces in Rough Neurocomputing

      • Andrzej Skowron
      Pages 13-22

  4. Soft Computing Pattern Recognition: Principles, Integrations and Data Mining

    1. Soft Computing Pattern Recognition: Principles, Integrations and Data Mining

      • Sankar K. Pal
      Pages 23-34

  5. Generalizations and New Theories

    1. Front Matter

      Pages 35-35
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    2. Generalization of Rough Sets Using Weak Fuzzy Similarity Relations

      • Rolly Intan, Y. Y. Yao, Masao Mukaidono
      Pages 37-46

    3. Two Directions toward Generalization of Rough Sets

      • Masahiro Inuiguchi, Tetsuzo Tanino
      Pages 47-57

    4. Two Generalizations of Multisets

      • Sadaaki Miyamoto
      Pages 59-68

    5. Interval Probability and Its Properties

      • Hideo Tanaka, Kazutomi Sugihara, Yutaka Maeda
      Pages 69-78

    6. On Fractal Dimension in Information Systems

      • Lech Polkowski
      Pages 79-87

    7. A Remark on Granular Reasoning and Filtration

      • Tetsuya Murai, Michinori Nakata, Yoshiharu Sato
      Pages 89-96

    8. Towards Discovery of Relevant Patterns from Parameterized Schemes of Information Granule Construction

      • Andrzej Skowron, JarosÅ‚aw Stepaniuk, James F. Peters
      Pages 97-108

    9. Approximate Markov Boundaries and Bayesian Networks: Rough Set Approach

      • Dominik ÅšlÄ™zak
      Pages 109-121

  6. Data Mining and Rough Sets

    1. Front Matter

      Pages 123-123
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    2. Mining High Order Decision Rules

      • Y. Y. Yao
      Pages 125-135

    3. Association Rules from a Point of View of Conditional Logic

      • Tetsuya Murai, Michinori Nakata, Yoshiharu Sato
      Pages 137-145

    4. Association Rules with Additional Semantics Modeled by Binary Relations

      • T. Y. Lin, Eric Louie
      Pages 147-156

    5. A Knowledge-Oriented Clustering Method Based on Indiscernibility Degree of Objects

      • Shoji Hirano, Shusaku Tsumoto
      Pages 157-166

    6. Some Effective Procedures for Data Dependencies in Information Systems

      • Hiroshi Sakai
      Pages 167-176

    7. Improving Rules Induced from Data Describing Self-Injurious Behaviors by Changing Truncation Cutoff and Strength

      • Jerzy W. Grzymala-Busse, Rachel L. Freeman
      Pages 177-185
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Keywords

About this book

After 20 years of pursuing rough set theory and its applications a look on its present state and further prospects is badly needed. The monograph Rough Set Theory and Granular Computing edited by Masahiro Inuiguchi, Shoji Hirano and Shusaku Tsumoto meets this demand. It presents the newest developments in this area and gives fair picture of the state of the art in this domain. Firstly, in the keynote papers by Zdzislaw Pawlak, Andrzej Skowron and Sankar K. Pal the relationship of rough sets with other important methods of data analysis -Bayes theorem, neuro computing and pattern recognitio- is thoroughly examined. Next, several interesting generalizations of the the­ ory and new directions of research are presented. Furthermore application of rough sets in data mining, in particular, rule induction methods based on rough set theory is presented and discussed. Further important issue dis­ cussed in the monograph is rough set based data analysis, including study of decisions making in conflict situations. Last but not least, some recent engi­ neering applications of rough set theory are given. They include a proposal of rough set processor architecture organization for fast implementation of ba­ sic rough set operations and discussion of results concerning advanced image processing for unmanned aerial vehicle. Thus the monograph beside presenting wide spectrum of ongoing research in this area also points out new emerging areas of study and applications, which makes it a valuable source of information to all interested in this do­ main.

Editors and Affiliations

  • Graduate School of Engineering, Osaka University, Osaka, Japan

    Masahiro Inuiguchi

  • Shimane Medical University, Izumo, Shimane-ken, Japan

    Shoji Hirano, Shusaku Tsumoto

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