Rough Sets and Current Trends in Computing

4th International Conference, RSCTC 2004, Uppsala, Sweden, June 1-5, 2004. Proceedings

  • Shusaku Tsumoto
  • Roman Słowiński
  • Jan Komorowski
  • Jerzy W. Grzymała-Busse

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3066)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 3066)

Table of contents

  1. Spatial Reasoning

    1. Shuliang Wang, Hanning Yuan, Guoqing Chen, Deren Li, Wenzhong Shi
      Pages 435-444
  2. Reduction

    1. Zhengren Qin, Guoyin Wang, Yu Wu, Xiaorong Xue
      Pages 445-454
    2. Tsau Young Lin, Ping Yin
      Pages 465-470
    3. Tian-rui Li, Ke-yun Qing, Ning Yang, Yang Xu
      Pages 471-476
    4. Chen Degang
      Pages 477-482
  3. Rule Induction

    1. Teresa Mroczek, Jerzy W. Grzymała-Busse, Zdzisław S. Hippe
      Pages 483-487
    2. Wojciech Rzasa, Artur Paluch, Zbigniew Suraj
      Pages 504-509
    3. Salvatore Greco, Benedetto Matarazzo, Nello Pappalardo, Roman Słowiński
      Pages 523-528
    4. Shoji Hirano, Shusaku Tsumoto
      Pages 529-538
  4. Rough Sets and Neural Network

    1. Bozena Kostek, Piotr Szczuko, Pawel Zwan
      Pages 539-548
    2. Wei-ji Su, Yu Su, Hai Zhao, Xiao-dan Zhang
      Pages 549-553
    3. Dominik Ślezak, Marcin S. Szczuka, Jakub Wróblewski
      Pages 554-560
  5. Clustering

    1. Dan Li, Jitender Deogun, William Spaulding, Bill Shuart
      Pages 573-579
    2. James F. Peters, Maciej Borkowski
      Pages 580-585
  6. Data Mining

    1. Jan G. Bazan, Marcin S. Szczuka, Arkadiusz Wojna, Marcin Wojnarski
      Pages 592-601
    2. J. W. Guan, David A. Bell, Dayou Liu
      Pages 602-609
    3. Hong-bin Shen, Shi-tong Wang, Jie Yang
      Pages 610-617
    4. Chorng-Shyong Ong, Jih-Jeng Huang, Gwo-Hshiung Tzeng
      Pages 624-629
    5. Ron Andrews, Stanislaw Bajcar, Jerzy W. Grzymała-Busse, Zdzisław S. Hippe, Chris Whiteley
      Pages 630-636
    6. Xumin Liu, Houkuan Huang, Weixiang Xu
      Pages 637-642
  7. Image and Signal Recognition

    1. Zheng Zheng, Hong Hu, Zhongzhi Shi
      Pages 659-664
    2. Gexiang Zhang, Haina Rong, Weidong Jin, Laizhao Hu
      Pages 665-670
    3. Seung Hak Rhee, Seungjo Han, Pan koo Kim, Muhammad Bilal Ahmad, Jong An Park
      Pages 671-678
    4. Lisa Lazareck, Sheela Ramanna
      Pages 679-684
  8. Information Retrieval

    1. Andrzej Czyzewski, Bozena Kostek
      Pages 691-698
    2. Yan Li, Simon Chi-Keung Shiu, Sankar Kumar Pal, James Nga-Kwok Liu
      Pages 699-707
    3. Hayri Sever, Zafer Bolat, Vijay V. Raghavan
      Pages 708-713
  9. Decision Support

    1. Malcolm J. Beynon, Benjamin Griffiths
      Pages 714-720
    2. Roman Siminski, Alicja Wakulicz-Deja
      Pages 721-726
    3. Barbara Fryc, Krzysztof Pancerz, Zbigniew Suraj
      Pages 733-742
  10. Adaptive and Opminization Methods

    1. Jiajin Huang, Ning Zhong, Chunnian Liu, Yiyu Yao
      Pages 743-751
    2. Ernestina Menasalvas, Socorro Millán, P. Gonzalez
      Pages 752-761
    3. Zhihua Cui, Jianchao Zeng
      Pages 762-767
    4. Haifeng Du, Licheng Jiao, Maoguo Gong, Ruochen Liu
      Pages 768-773
    5. Jing Liu, Weicai Zhong, Li-cheng Jiao, Fang Liu
      Pages 774-779
  11. Bioinformatics

    1. Filip Ginter, Tapio Pahikkala, Sampo Pyysalo, Jorma Boberg, Jouni Järvinen, Tapio Salakoski
      Pages 780-785

About these proceedings


In recent years rough set theory has attracted the attention of many researchers and practitioners all over the world, who have contributed essentially to its development and applications. Weareobservingagrowingresearchinterestinthefoundationsofroughsets, including the various logical, mathematical and philosophical aspects of rough sets. Some relationships have already been established between rough sets and other approaches, and also with a wide range of hybrid systems. As a result, rough sets are linked with decision system modeling and analysis of complex systems, fuzzy sets, neural networks, evolutionary computing, data mining and knowledge discovery, pattern recognition, machine learning, and approximate reasoning. In particular, rough sets are used in probabilistic reasoning, granular computing (including information granule calculi based on rough mereology), intelligent control, intelligent agent modeling, identi?cation of autonomous s- tems, and process speci?cation. Methods based on rough set theory alone or in combination with other - proacheshavebeendiscoveredwith awide rangeofapplicationsinsuchareasas: acoustics, bioinformatics, business and ?nance, chemistry, computer engineering (e.g., data compression, digital image processing, digital signal processing, p- allel and distributed computer systems, sensor fusion, fractal engineering), de- sion analysis and systems, economics, electrical engineering (e.g., control, signal analysis, power systems), environmental studies, informatics, medicine, mole- lar biology, musicology, neurology, robotics, social science, software engineering, spatial visualization, Web engineering, and Web mining.


Alignment Pattern Mining algorithms bioinformatics database decision making evolutionary algorithm evolutionary computing granular computing intelligent control modeling neural computing rough sets statistical inference uncertain reasoning

Editors and affiliations

  • Shusaku Tsumoto
    • 1
  • Roman Słowiński
    • 2
  • Jan Komorowski
    • 3
  • Jerzy W. Grzymała-Busse
    • 4
  1. 1.Shimane UniversityShimaneJapan
  2. 2.Systems Research InstitutePolish Academy of SciencesWarsawPoland
  3. 3.The Linnaeus Centre for BioinformaticsUppsala UniversityUppsalaSweden
  4. 4.Institute of Computer SciencePolish Academy of SciencesWarsawPoland

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2004
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-22117-3
  • Online ISBN 978-3-540-25929-9
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site
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