© 2014

Rough Sets and Knowledge Technology

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

  • Duoqian Miao
  • Witold Pedrycz
  • Dominik Ślȩzak
  • Georg Peters
  • Qinghua Hu
  • Ruizhi Wang
Conference proceedings RSKT 2014

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

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 8818)

Table of contents

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

    1. Front Matter
      Pages 1-1
    2. Davide Ciucci, Tamás Mihálydeák, Zoltán Ernő Csajbók
      Pages 15-26
    3. Vinay Gautam, Vijay K. Yadav, Anupam K. Singh, S. P. Tiwari
      Pages 39-48
    4. Caihui Liu, Meizhi Wang, Yujiang Liu, Min Wang
      Pages 59-68
  3. Attribute Reduction and Feature Selection

    1. Front Matter
      Pages 75-75
    2. Wei Zhang, Duoqian Miao, Can Gao, Xiaodong Yue
      Pages 77-88
    3. Feifei Xu, Zhongqin Bi, Jingsheng Lei
      Pages 89-100
    4. Anjing Fan, Hong Zhao, William Zhu
      Pages 101-110
    5. Lingjun Zhang, Qinghua Hu, Jie Duan, Xiaoxue Wang
      Pages 121-128
    6. Junxia Niu, Hong Zhao, William Zhu
      Pages 129-138
    7. Ying Xia, Qiang Lu, JiangFan Feng, Hae-Young Bae
      Pages 149-157
  4. Applications of Rough Sets

    1. Front Matter
      Pages 159-159
    2. Ying Zhou, Jing Tao Yao
      Pages 161-172

About these proceedings


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.


Web-based learning approximation big data data mining decision rules decision systems granular computing knowledge representation and reasoning machine learning neural networks pattern recognition recommender system rough sets three-way decisions uncertainty analysis uncertainty measures

Editors and affiliations

  • Duoqian Miao
    • 1
  • Witold Pedrycz
    • 2
  • Dominik Ślȩzak
    • 3
  • Georg Peters
    • 4
  • Qinghua Hu
    • 5
  • Ruizhi Wang
    • 6
  1. 1.Tongji UniversityShanghaiChina
  2. 2.Department of Electrical and Computer EnUniversity of AlbertaEdmontonCanada
  3. 3.University of WarsawWarsawPoland
  4. 4.University of Applied SciencesMünchenGermany
  5. 5.Tianjin UniversityTianjinChina
  6. 6.Tongji UniversityShanghaiChina

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