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Data Mining and Knowledge Management

Chinese Academy of Sciences Symposium CASDMKD 2004, Beijing, China, July 12-14, 2004, Revised Paper

  • Conference proceedings
  • © 2004

Overview

Editors:
  1. Yong Shi

    1. Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing 100080, China; College of Information Science and Technology, University of Nebraska at Omaha, Omaha, USA

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  2. Weixuan Xu

    1. Institute of Policy & Management, Chinese Academy of Sciences, Beijing, P.R. China

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  3. Zhengxin Chen

    1. College of Information Science and Technology, University of Nebraska at Omaha, USA

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

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: CASDMKM 2004.

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Table of contents (28 papers)

  1. Front Matter

    Pages I-XIII
    Download chapter PDF

  2. Keynote Lectures

    1. Visualization-Based Data Mining Tool and Its Web Application

      • Alexander V. Lotov, Alexander A. Kistanov, Alexander D. Zaitsev
      Pages 1-10

    2. Knowledge Management, Habitual Domains, and Innovation Dynamics

      • P. L. Yu, T. C. Lai
      Pages 11-21

    3. Knowledge-Information Circulation Through the Enterprise: Forward to the Roots of Knowledge Management

      • Milan Zeleny
      Pages 22-33

  3. Data Mining Methodology

    1. A Hybrid Nonlinear Classifier Based on Generalized Choquet Integrals

      • Zhenyuan Wang, Hai-Feng Guo, Yong Shi, Kwong-Sak Leung
      Pages 34-40

    2. Fuzzy Classification Using Self-Organizing Map and Learning Vector Quantization

      • Ning Chen
      Pages 41-50

    3. Solving Discriminant Models Using Interior Point Algorithm

      • Siming Huang, Guoliang Yang, Chao Su
      Pages 51-60

    4. A Method for Solving Optimization Problem in Continuous Space Using Improved Ant Colony Algorithm

      • Ling Chen, Jie Shen, Ling Qin, Jin Fan
      Pages 61-70

  4. Practical Issues of Data Mining

    1. Data Set Balancing

      • David L. Olson
      Pages 71-80

    2. Computation of Least Square Estimates Without Matrix Manipulation

      • Yachen Lin, Chung Chen
      Pages 81-89

    3. Ensuring Serializability for Mobile Data Mining on Multimedia Objects

      • Shin Parker, Zhengxin Chen, Eugene Sheng
      Pages 90-98

  5. Data Mining for Bioinformatics

    1. “Copasetic Clustering”: Making Sense of Large-Scale Images

      • Karl Fraser, Paul O’Neill, Zidong Wang, Xiaohui Liu
      Pages 99-108

    2. Ranking Gene Regulatory Network Models with Microarray Data and Bayesian Network

      • Hongqiang Li, Mi Zhou, Yan Cui
      Pages 109-118

    3. On Efficiency of Experimental Designs for Single Factor cDNA Microarray Experiments

      • Xiao Yang, Keying Ye
      Pages 119-127

  6. Data Mining Applications

    1. Data Mining Approach in Scientific Research Organizations Evaluation Via Clustering

      • Jingli Liu, Jianping Li, Weixuan Xu, Yong Shi
      Pages 128-134

    2. Heuristics to Scenario-Based Capacity Expansion Problem of PWB Assembly Systems

      • Zhongsheng Hua, Liang Liang
      Pages 135-144

    3. A Multiple-Criteria Quadratic Programming Approach to Network Intrusion Detection

      • Gang Kou, Yi Peng, Yong Shi, Zhengxin Chen, Xiaojun Chen
      Pages 145-153

    4. classifications of Credit Cardholder Behavior by Using Multiple Criteria Non-linear Programming

      • Jing He, Yong Shi, Weixuan Xu
      Pages 154-163

    5. Multiple Criteria Linear Programming Data Mining Approach: An Application for Bankruptcy Prediction

      • Wikil Kwak, Yong Shi, John J. Cheh, Heeseok Lee
      Pages 164-173

  7. Knowledge Management for Enterprise

    1. Coordination and Cooperation in Manufacturer-Retailer Supply Chains

      • Zhimin Huang, Susan X. Li
      Pages 174-186
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About this book

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

Editors and Affiliations

  • Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing 100080, China; College of Information Science and Technology, University of Nebraska at Omaha, Omaha, USA

    Yong Shi

  • Institute of Policy & Management, Chinese Academy of Sciences, Beijing, P.R. China

    Weixuan Xu

  • College of Information Science and Technology, University of Nebraska at Omaha, USA

    Zhengxin Chen

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