Rough Set and Knowledge Technology

1. Front Matter

   PDF

2. Keynote Papers

   1. Mining Incomplete Data—A Rough Set Approach

      • Jerzy W. Grzymała-Busse

      Pages 1-7

   2. Uncertainty and Feature Selection in Rough Set Theory

      • Jiye Liang

      Pages 8-15

   3. Towards Designing Human Centric Systems: A New View at System Modeling with Granular Membership Grades

      • Witold Pedrycz

      Pages 16-16

   4. Sufficiently Near Sets of Neighbourhoods

      • James F. Peters

      Pages 17-24

3. Invited Tutorial

   1. History of Set Theory and Its Extensions in the Context of Soft Computing

      • Sarjerao Nimse, Pawan Lingras

      Pages 25-25

4. Attribute Reduction and Feature Selection

   1. Comparison of Classical Dimensionality Reduction Methods with Novel Approach Based on Formal Concept Analysis

      • Eduard Bartl, Hana Rezankova, Lukas Sobisek

      Pages 26-35

   2. Rule-Based Estimation of Attribute Relevance

      • Jerzy Błaszczyński, Roman Słowiński, Robert Susmaga

      Pages 36-44

   3. Applications of Approximate Reducts to the Feature Selection Problem

      • Andrzej Janusz, Sebastian Stawicki

      Pages 45-50

   4. Dependence and Algebraic Structure of Formal Contexts

      • Tong-Jun Li, Ying-Xue Wu, Xiaoping Yang

      Pages 51-56

   5. Optimal Sub-Reducts with Test Cost Constraint

      • Fan Min, William Zhu

      Pages 57-62

   6. An Efficient Fuzzy-Rough Attribute Reduction Approach

      • Yuhua Qian, Chao Li, Jiye Liang

      Pages 63-70

   7. A Novel Attribute Reduction Approach Based on the Object Oriented Concept Lattice

      • Mingwen Shao, Li Guo, Lan Li

      Pages 71-80

   8. Rough-Set-Inspired Feature Subset Selection, Classifier Construction, and Rule Aggregation

      • Dominik Ślęzak, Sebastian Widz

      Pages 81-88

   9. A Constructive Feature Induction Mechanism Founded on Evolutionary Strategies with Fitness Functions Generated on the Basis of Decision Trees

      • Mariusz Wrzesień, Wiesław Paja, Krzysztof Pancerz

      Pages 89-94

   10. An Efficient Fuzzy Rough Approach for Feature Selection

       • Feifei Xu, Weiguo Pan, Lai Wei, Haizhou Du

       Pages 95-100

   11. Partitions, Coverings, Reducts and Rule Learning in Rough Set Theory

       • Yiyu Yao, Rong Fu

       Pages 101-109

   12. A Rough Set Approach to Feature Selection Based on Relative Decision Entropy

       • Lin Zhou, Feng Jiang

       Pages 110-119

5. Generalized Rough Set Models

   1. A Variable Precision Covering Generalized Rough Set Model

      • Xinwei Zheng, Jian-Hua Dai

      Pages 120-125

   2. Dominance-Based Rough Set Approach on Pairwise Comparison Tables to Decision Involving Multiple Decision Makers

      • Salvatore Greco, Benedetto Matarazzo, Roman Słowiński

      Pages 126-135

This book constitutes the refereed proceedings of the 6th International Conference on Rough Sets and Knowledge Technology, RSKT 2011, held in Banff, Canada, in September 2011. The 89 revised full papers presented together with 3 keynote lectures and 1 invited tutorial session were carefully reviewed and selected from 229 submissions. The papers are organized in topical sections on attribute reduction and feature selection, generalized rough set models, machine learning with rough and hybrid techniques, knowledge technology and intelligent systems and applications.

• complex networks
• decision support systems
• fuzzy rough sets
• quality of service (QoS)
• similarity measure

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

  JingTao Yao

• Department of Applied Computer Science, University of Winnipeg, Winnipeg, Canada

  Sheela Ramanna

• Institute of Computer Science & Technology, Chongqing University of Posts and Telecommunications, Chongqing, P.R. China

  Guoyin Wang

• Chair of Computer Science, University of Rzeszów, Poland

  Zbigniew Suraj

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