Data Mining and Knowledge Management

Chinese Academy of Sciences Symposium CASDMKM 2004, Beijing, China, July 12-14, 2004. Revised Papers

  • Yong Shi
  • Weixuan Xu
  • Zhengxin Chen
Conference proceedings CASDMKM 2004

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3327)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 3327)

Table of contents

  1. Front Matter
  2. Keynote Lectures

  3. Data Mining Methodology

  4. Practical Issues of Data Mining

    1. David L. Olson
      Pages 71-80
    2. Shin Parker, Zhengxin Chen, Eugene Sheng
      Pages 90-98
  5. Data Mining for Bioinformatics

    1. Karl Fraser, Paul O’Neill, Zidong Wang, Xiaohui Liu
      Pages 99-108
  6. Data Mining Applications

  7. Knowledge Management for Enterprise

    1. Zhengqing Tang, Jianping Li, Zetao Yan
      Pages 195-203
    2. Jun Tian, Shaochuan Cheng, Kanliang Wang, Yingluo Wang
      Pages 204-212
  8. Risk Management

  9. Integration of Data Mining and Knowledge Management

    1. Shouyang Wang, Lean Yu, K. K. Lai
      Pages 233-242
    2. Jichang Dong, K. K. Lai, Shouyang Wang
      Pages 254-262
  10. Back Matter

About these proceedings


criteria linear and nonlinear programming has proven to be a very useful approach. • Knowledge management for enterprise: These papers address various issues related to the application of knowledge management in corporations using various techniques. A particular emphasis here is on coordination and cooperation. • Risk management: Better knowledge management also requires more advanced techniques for risk management, to identify, control, and minimize the impact of uncertain events, as shown in these papers, using fuzzy set theory and other approaches for better risk management. • Integration of data mining and knowledge management: As indicated earlier, the integration of these two research fields is still in the early stage. Nevertheless, as shown in the papers selected in this volume, researchers have endearored to integrate data mining methods such as neural networks with various aspects related to knowledge management, such as decision support systems and expert systems, for better knowledge management. September 2004 Yong Shi Weixuan Xu Zhengxin Chen CASDMKM 2004 Organization Hosted by Institute of Policy and Management at the Chinese Academy of Sciences Graduate School of the Chinese Academy of Sciences International Journal of Information Technology and Decision Making Sponsored by Chinese Academy of Sciences National Natural Science Foundation of China University of Nebraska at Omaha, USA Conference Chairs Weixuan Xu, Chinese Academy of Sciences, China Yong Shi, University of Nebraska at Omaha, USA Advisory Committee


bioinformatics bromedical data analysis classification clustering data analysis data mining data visualisation enterprise knowledge systems knowledge discovery knowledge management microarray data analysis multimedia data mining risk analysis

Editors and affiliations

  • Yong Shi
    • 1
  • Weixuan Xu
    • 2
  • Zhengxin Chen
    • 3
  1. 1.Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing 100080, China; College of Information Science and TechnologyUniversity of Nebraska at OmahaOmahaUSA
  2. 2.Institute of Policy & ManagementChinese Academy of SciencesBeijingP.R. China
  3. 3.College of Information Science and TechnologyUniversity of Nebraska at OmahaUSA

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag Berlin Heidelberg 2005
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-23987-1
  • Online ISBN 978-3-540-30537-8
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site