Foundations and Novel Approaches in Data Mining

  • Editors
  • Tsau Young Lin
  • Setsuo Ohsuga
  • Churn-Jung Liau
  • Xiaohua Hu

Part of the Studies in Computational Intelligence book series (SCI, volume 9)

Table of contents

  1. Front Matter
  2. Yiyu Yao, Yaohua Chen, Xuedong Yang
    Pages 41-59
  3. J. T. Yao, Y. Y. Yao, Y. Zhao
    Pages 75-97
  4. Ernestina Menasalvas1, Anita Wasilewska2
    Pages 99-126
  5. Jiaqi Wang, Chengqi Zhang, Xindong Wu, Hongwei Qi, Jue Wang
    Pages 129-141
  6. Agnieszka Dardzińska, Zbigniew W. Raśs
    Pages 143-153
  7. Jan Rauch, Milan šimůnek, Václav Lín
    Pages 155-167
  8. Rafal A. Angryk, Frederick E. Petry
    Pages 169-196
  9. Jerzy W. Grzymala-Busse
    Pages 197-212
  10. Justin Zhan, LiWu Chang, Stan Matwin
    Pages 213-227
  11. Mitja Lenič, Petra Povalej, Peter Kokol
    Pages 229-242
  12. Ching-Yao Wang, Tzung-Pei Hong, Shian-Shyong Tseng
    Pages 243-257
  13. Ling Zhang Bo Zhang, Bo Zhang
    Pages 259-269
  14. Qiankun Zhao, Sourav S. Bhowmick, Sanjay Madria
    Pages 272-289
  15. Kwang-Hoon Kim, Clarence A. Ellis
    Pages 289-310
  16. Mei-Ling Shyu, Shu-Ching Chen, Kanoksri Sarinnapakorn, LiWu Chang
    Pages 311-329
  17. Vincent S. M. Tseng, Yen-Lo Chen
    Pages 363-376

About this book


Data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor” syndrome. Currently, application oriented engineers are only concerned with their immediate problems, which results in an ad hoc method of problem solving. Researchers, on the other hand, lack an understanding of the practical issues of data-mining for realworld problems and often concentrate on issues that are of no significance to the practitioners. In this volume, we hope to remedy problems by (1) presenting a theoretical foundation of data-mining, and (2) providing important new directions for data-mining research. A set of well respected data mining theoreticians were invited to present their views on the fundamental science of data mining. We have also called on researchers with practical data mining experiences to present new important data-mining topics.


Statistica classification data mining databases fuzzy knowledge discovery modeling problem solving

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin/Heidelberg 2006
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-540-28315-7
  • Online ISBN 978-3-540-31229-1
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site
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