Rough Sets and Knowledge Technology

8th International Conference, RSKT 2013, Halifax, NS, Canada, October 11-14, 2013, Proceedings

  • Pawan Lingras
  • Marcin Wolski
  • Chris Cornelis
  • Sushmita Mitra
  • Piotr Wasilewski

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8171)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 8171)

Table of contents

  1. Front Matter
  2. Tutorial

  3. History and Future of Rough Sets

    1. Hiroshi Sakai, Mao Wu, Naoto Yamaguchi, Michinori Nakata
      Pages 7-15
    2. JingTao Yao, Yan Zhang
      Pages 28-40
    3. Patrick G. Clark, Jerzy W. Grzymała-Busse, Wojciech Rząsa
      Pages 41-52
    4. Guoyin Wang, Changlin Xu, Hong Yu
      Pages 53-65
  4. Foundations and Probabilistic Rough Sets

    1. Jingqian Wang, William Zhu
      Pages 75-86
    2. Ryszard Janicki, Adam Lenarčič
      Pages 87-98
    3. Tamás Mihálydeák, Zoltán Ernő Csajbók
      Pages 99-108
    4. Mei-Zheng Li, Guoyin Wang, Jin Wang
      Pages 109-120
    5. Bing Zhou, Yiyu Yao
      Pages 121-132
    6. Yoshifumi Kusunoki, Jerzy Błaszczyński, Masahiro Inuiguchi, Roman Słowiński
      Pages 133-144
    7. Nouman Azam, JingTao Yao
      Pages 145-153
  5. Rules, Reducts, Ensembles

    1. Motoyuki Ohki, Masahiro Inuiguchi
      Pages 166-177
    2. Leijun Li, Qinghua Hu, Xiangqian Wu, Daren Yu
      Pages 178-187
    3. Shusaku Tsumoto, Shoji Hirano
      Pages 188-199
    4. Sebastian Stawicki, Dominik Ślęzak
      Pages 200-212

About these proceedings

Introduction

This book constitutes the thoroughly refereed conference proceedings of the 8th International Conference on Rough Sets and Knowledge Technology, RSKT 2013, held in Halifax, Canada in October 2013 as one of the co-located conferences of the 2013 Joint Rough Set Symposium, JRS 2013. The 69 papers (including 44 regular and 25 short papers) included in the JRS proceedings (LNCS 8170 and LNCS 8171) were carefully reviewed and selected from 106 submissions. The papers in this volume cover topics such as history and future of rough sets; foundations and probabilistic rough sets; rules, reducts, ensembles; new trends in computing; three-way decision rough sets; and learning, predicting, modeling.

Keywords

GPU approximation decision rules machine learning pattern recognition

Editors and affiliations

  • Pawan Lingras
    • 1
  • Marcin Wolski
    • 2
  • Chris Cornelis
    • 3
  • Sushmita Mitra
    • 4
  • Piotr Wasilewski
    • 5
  1. 1.Saint Mary’s UniversityHalifaxCanada
  2. 2.Maria Curie-Skłodowska UniversityLublinPoland
  3. 3.University of GranadaSpain
  4. 4.Indian Statistical InstituteKolkataIndia
  5. 5.University of WarsawWarsawPoland

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-41299-8
  • Copyright Information Springer-Verlag Berlin Heidelberg 2013
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-642-41298-1
  • Online ISBN 978-3-642-41299-8
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book