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Rough Sets, Fuzzy Sets, Data Mining and Granular Computing

13th International Conference, RSFDGrC 2011, Moscow, Russia, June 25-27, 2011, Proceedings

  • Conference proceedings
  • © 2011

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Editors:
  1. Sergei O. Kuznetsov

    1. State University Higher School of Economics, Moscow, Russia

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  2. Dominik Ślęzak

    1. Institute of Mathematics, University of Warsaw, Warsaw, Poland

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  3. Daryl H. Hepting

    1. Department of Computer Science, University of Regina, Regina, Canada

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  4. Boris G. Mirkin

    1. Birbeck University of London, London, UK

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  • Fast track conference proceedings
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 6743)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: RSFDGrC 2011.

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About this book

This book constitutes the refereed proceedings of the 13th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2011, held in Moscow, Russia in June 2011.
The 49 revised full papers presented together with 5 invited and 2 tutorial papers were carefully reviewed and selected from a total of 83 submissions. The papers are organized in topical sections on rough sets and approximations, coverings and granules, fuzzy set models, fuzzy set applications, compound values, feature selection and reduction, clusters and concepts, rules and trees, image processing, and interactions and visualization.

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Table of contents (56 papers)

  1. Front Matter

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  3. Tutorial Papers

    1. The Use of Rough Set Methods in Knowledge Discovery in Databases

      • Marcin Szczuka
      Pages 28-30

    2. Fuzzy-Rough Data Mining

      • Richard Jensen
      Pages 31-35

  4. Rough Sets and Approximations

    1. Dual Rough Approximations in Information Tables with Missing Values

      • Michinori Nakata, Hiroshi Sakai
      Pages 36-43

    2. Rough Sets and General Basic Set Assignments

      • Tong-Jun Li, Wei-Zhi Wu
      Pages 44-51

    3. General Tool-Based Approximation Framework Based on Partial Approximation of Sets

      • Zoltán Csajbók, Tamás Mihálydeák
      Pages 52-59

    4. An Improved Variable Precision Model of Dominance-Based Rough Set Approach

      • Weibin Deng, Guoyin Wang, Feng Hu
      Pages 60-67

    5. Rough Numbers and Rough Regression

      • Marcin Michalak
      Pages 68-71

  5. Coverings and Granules

    1. Covering Numbers in Covering-Based Rough Sets

      • Shiping Wang, Fan Min, William Zhu
      Pages 72-78

    2. On Coverings of Rough Transformation Semigroups

      • S. P. Tiwari, Shambhu Sharan
      Pages 79-86

    3. Covering Rough Set Model Based on Multi-granulations

      • Caihui Liu, Duoqian Miao
      Pages 87-90

    4. A Descriptive Language Based on Granular Computing – Granular Logic

      • Qing Liu, Lan Liu
      Pages 91-94

  6. Fuzzy Set Models

    1. Optimization and Adaptation of Dynamic Models of Fuzzy Relational Cognitive Maps

      • Grzegorz Słoń, Alexander Yastrebov
      Pages 95-102

    2. Sensitivity Analysis for Fuzzy Linear Programming Problems

      • Amit Kumar, Neha Bhatia
      Pages 103-110

    3. Estimation of Parameters of the Empirically Reconstructed Fuzzy Model of Measurements

      • Tatiana Kopit, Alexey Chulichkov
      Pages 111-118
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Other volumes

  1. Rough Sets, Fuzzy Sets, Data Mining and Granular Computing

Editors and Affiliations

  • State University Higher School of Economics, Moscow, Russia

    Sergei O. Kuznetsov

  • Institute of Mathematics, University of Warsaw, Warsaw, Poland

    Dominik Ślęzak

  • Department of Computer Science, University of Regina, Regina, Canada

    Daryl H. Hepting

  • Birbeck University of London, London, UK

    Boris G. Mirkin

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