Table of contents

  1. Front Matter
  2. Setsuo Ohsuga
    Pages 1-19
  3. Hye-Chung (Monica) Kum, Susan Paulsen, Wei Wang
    Pages 43-70
  4. Murlikrishna Viswanathan, Kotagiri Ramamohanarao
    Pages 71-86
  5. Tuan-Fang Fan, Duen-Ren Liu, Churn-Jung Liau
    Pages 119-130
  6. Yohji Shidara, Mineichi Kudo, Atsuyoshi Nakamura
    Pages 161-170
  7. QingXiang Wu, David Bell, Martin McGinnity, Gongde Guo
    Pages 171-184
  8. Paul Cotofrei, Kilian Stoffel
    Pages 185-210
  9. Jan Rauch, Milan Šimůnek
    Pages 211-231
  10. Vladimir Gorodetsky, Oleg Karsaev, Vladimir Samoilov
    Pages 233-264
  11. Mitja Lenič, Peter Kokol, Milan Zorman, Petra Povalej, Bruno Stiglic, Ryuichi Yamamoto
    Pages 305-318
  12. Tianhao Wu, Faisal M. Khan, Todd A. Fisher, Lori A. Shuler, William M. Pottenger
    Pages 319-331
  13. April Kontostathis, William M. Pottenger, Brian D. Davison
    Pages 333-346
  14. Petr Strossa, Zdeněk Černý, Jan Rauch
    Pages 347-361
  15. S. Millán, E. Menasalvas, M. Hadjimichael, E. Hochsztain
    Pages 363-375

About this book


Foundations of Data Mining and Knowledge Discovery contains the latest results and new directions in data mining research. Data mining, which integrates various technologies, including computational intelligence, database and knowledge management, machine learning, soft computing, and statistics, is one of the fastest growing fields in computer science. Although many data mining techniques have been developed, further development of the field requires a close examination of its foundations. This volume presents the results of investigations into the foundations of the discipline, and represents the state-of-the-art for much of the current research. This book will prove extremely valuable and fruitful for data mining researchers, no matter whether they would like to uncover the fundamental principles behind data mining, or apply the theories to practical applications.


Computer Foundations of Data Mining General Knowledge Discovery Methods of Data Mining Pattern Mining data mining database databases intelligence knowledge management learning logic machine learning model statistics

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin/Heidelberg 2005
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-540-26257-2
  • Online ISBN 978-3-540-32408-9
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site
Industry Sectors
Finance, Business & Banking
IT & Software
Consumer Packaged Goods