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Rough Sets and Knowledge Technology

9th International Conference, RSKT 2014, Shanghai, China, October 24-26, 2014, Proceedings

  • Conference proceedings
  • © 2014

Overview

Editors:
  1. Duoqian Miao

    1. Tongji University, Shanghai, China

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  2. Witold Pedrycz

    1. Department of Electrical and Computer En, University of Alberta, Edmonton, Canada

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  3. Dominik Ślȩzak

    1. University of Warsaw, Warsaw, Poland

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  4. Georg Peters

    1. University of Applied Sciences, München, Germany

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  5. Qinghua Hu

    1. Tianjin University, Tianjin, China

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  6. Ruizhi Wang

    1. Tongji University, Shanghai, China

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 8818)

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

Included in the following conference series:

Conference proceedings info: RSKT 2014.

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Table of contents (78 papers)

  1. Front Matter

    Pages 1-27
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  2. Foundations and Generalizations of Rough Sets

    1. Front Matter

      Pages 1-1
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    2. Generalized Dominance-Based Rough Set Model for the Dominance Intuitionistic Fuzzy Information Systems

      • Xiaoxia Zhang, Degang Chen
      Pages 3-14

    3. On Definability and Approximations in Partial Approximation Spaces

      • Davide Ciucci, Tamás Mihálydeák, Zoltán Ernő Csajbók
      Pages 15-26

    4. Many-Valued Rough Sets Based on Tied Implications

      • Moataz El-Zekey
      Pages 27-38

    5. On the Topological Structure of Rough Soft Sets

      • Vinay Gautam, Vijay K. Yadav, Anupam K. Singh, S. P. Tiwari
      Pages 39-48

    6. Knowledge Granulation in Interval-Valued Information Systems Based on Maximal Consistent Blocks

      • Nan Zhang, Xiaodong Yue
      Pages 49-58

    7. Multi-granulation Rough Sets Based on Central Sets

      • Caihui Liu, Meizhi Wang, Yujiang Liu, Min Wang
      Pages 59-68

    8. Rough Set Theory on Topological Spaces

      • K. Anitha
      Pages 69-74

  3. Attribute Reduction and Feature Selection

    1. Front Matter

      Pages 75-75
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    2. Co-training Based Attribute Reduction for Partially Labeled Data

      • Wei Zhang, Duoqian Miao, Can Gao, Xiaodong Yue
      Pages 77-88

    3. Approximate Reduction for the Interval-Valued Decision Table

      • Feifei Xu, Zhongqin Bi, Jingsheng Lei
      Pages 89-100

    4. Global Best Artificial Bee Colony for Minimal Test Cost Attribute Reduction

      • Anjing Fan, Hong Zhao, William Zhu
      Pages 101-110

    5. Reductions of Intuitionistic Fuzzy Covering Systems Based on Discernibility Matrices

      • Tao Feng, Jusheng Mi
      Pages 111-120

    6. Multi-label Feature Selection with Fuzzy Rough Sets

      • Lingjun Zhang, Qinghua Hu, Jie Duan, Xiaoxue Wang
      Pages 121-128

    7. A Logarithmic Weighted Algorithm for Minimal Test Cost Attribute Reduction

      • Junxia Niu, Hong Zhao, William Zhu
      Pages 129-138

    8. Attribute Reduction in Object Oriented Concept Lattices Based on Congruence Relations

      • Xia Wang, Wei-Zhi Wu
      Pages 139-148

    9. An Explicit Sparse Mapping for Nonlinear Dimensionality Reduction

      • Ying Xia, Qiang Lu, JiangFan Feng, Hae-Young Bae
      Pages 149-157

  4. Applications of Rough Sets

    1. Front Matter

      Pages 159-159
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    2. A Web-Based Learning Support System for Rough Sets

      • Ying Zhou, Jing Tao Yao
      Pages 161-172
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  1. Rough Sets and Knowledge Technology

Keywords

About this book

This book constitutes the thoroughly refereed conference proceedings of the 9th International Conference on Rough Sets and Knowledge Technology, RSKT 2014, held in Shanghai, China, in October 2014. The 70 papers presented were carefully reviewed and selected from 162 submissions. The papers in this volume cover topics such as foundations and generalizations of rough sets, attribute reduction and feature selection, applications of rough sets, intelligent systems and applications, knowledge technology, domain-oriented data-driven data mining, uncertainty in granular computing, advances in granular computing, big data to wise decisions, rough set theory, and three-way decisions, uncertainty, and granular computing.

Editors and Affiliations

  • Tongji University, Shanghai, China

    Duoqian Miao, Ruizhi Wang

  • Department of Electrical and Computer En, University of Alberta, Edmonton, Canada

    Witold Pedrycz

  • University of Warsaw, Warsaw, Poland

    Dominik Ślȩzak

  • University of Applied Sciences, München, Germany

    Georg Peters

  • Tianjin University, Tianjin, China

    Qinghua Hu

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