Data Mining and Knowledge Management [electronic resource] : Chinese Academy of Sciences Symposium CASDMKD 2004, Beijing, China, July 12-14, 2004, Revised Paper /
CASDMKM 2004(2004 :Beijing, China)
Shi, Yong.editor.
Xu, Weixuan.editor.
Chen, Zhengxin.editor.
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.
Bibliographic Level Mode of Issuance: Monograph
Includes bibliographical references and index.
Keynote Lectures -- Visualization-Based Data Mining Tool and Its Web Application -- Knowledge Management, Habitual Domains, and Innovation Dynamics -- Knowledge-Information Circulation Through the Enterprise: Forward to the Roots of Knowledge Management -- Data Mining Methodology -- A Hybrid Nonlinear Classifier Based on Generalized Choquet Integrals -- Fuzzy Classification Using Self-Organizing Map and Learning Vector Quantization -- Solving Discriminant Models Using Interior Point Algorithm -- A Method for Solving Optimization Problem in Continuous Space Using Improved Ant Colony Algorithm -- Practical Issues of Data Mining -- Data Set Balancing -- Computation of Least Square Estimates Without Matrix Manipulation -- Ensuring Serializability for Mobile Data Mining on Multimedia Objects -- Data Mining for Bioinformatics -- “Copasetic Clustering”: Making Sense of Large-Scale Images -- Ranking Gene Regulatory Network Models with Microarray Data and Bayesian Network -- On Efficiency of Experimental Designs for Single Factor cDNA Microarray Experiments -- Data Mining Applications -- Data Mining Approach in Scientific Research Organizations Evaluation Via Clustering -- Heuristics to Scenario-Based Capacity Expansion Problem of PWB Assembly Systems -- A Multiple-Criteria Quadratic Programming Approach to Network Intrusion Detection -- classifications of Credit Cardholder Behavior by Using Multiple Criteria Non-linear Programming -- Multiple Criteria Linear Programming Data Mining Approach: An Application for Bankruptcy Prediction -- Knowledge Management for Enterprise -- Coordination and Cooperation in Manufacturer-Retailer Supply Chains -- Development of Enterprises’ Capability Based on Cooperative Knowledge Network -- Information Mechanism, Knowledge Management and Arrangement of Corporate Stratagem -- An Integrating Model of Experts’ Opinions -- Risk Management -- Cartographic Representation of the Uncertainty Related to Natural Disaster Risk: Overview and State of the Art -- A Multi-objective Decision-Making Method for Commercial Banks Loan Portfolio -- A Multi-factors Evaluation Method on Credit Evaluation of Commerce Banks -- Integration of Data Mining and Knowledge Management -- A Novel Hybrid AI System Framework for Crude Oil Price Forecasting -- A Neural Network and Web-Based Decision Support System for Forex Forecasting and Trading -- XML-Based Schemes for Business Project Portfolio Selection.
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.
Artificial intelligence.
Database management.
Application software.
Information technology.
Business—Data processing.
Artificial Intelligence.
Database Management.
Information Systems Applications (incl. Internet).
Computer Appl. in Administrative Data Processing.
IT in Business.
Lecture notes in computer science