Data Mining and Knowledge Management Chinese Academy of Sciences Sym
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 pa
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Subseries of Lecture Notes in Computer Science
3327
Yong Shi Weixuan Xu Zhengxin Chen (Eds.)
Data Mining and Knowledge Management Chinese Academy of Sciences Symposium CASDMKM 2004 Beijing, China, July 12-14, 2004 Revised Papers
13
Series Editors Jaime G. Carbonell, Carnegie Mellon University, Pittsburgh, PA, USA Jörg Siekmann, University of Saarland, Saarbrücken, Germany Volume Editors Yong Shi Graduate University of Chinese Academy of Sciences CAS Research Center on Data Technology and Knowledge Economy No. 80 Zhongguancun East Rd., Beijing, China 100080 E-mail: [email protected] and University of Nebraska at Omaha College of Information Science and Technology Omaha, NE 68182, USA E-mail: [email protected] Weixuan Xu Chinese Academy of Sciences, Institute of Policy and Management 55 Zhongguancun Rd., Beijing 100080, China E-mail: [email protected] Zhengxin Chen University of Nebraska at Omaha, College of Information Science and Technology Omaha, NE 68182, USA E-mail: [email protected]
Library of Congress Control Number: 2004117657
CR Subject Classification (1998): I.2, H.2.8, H.4, J.1 ISSN 0302-9743 ISBN 3-540-23987-1 Springer Berlin Heidelberg New York This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation, broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. Springer is a part of Springer Science+Business Media springeronline.com © Springer-Verlag Berlin Heidelberg 2004 Printed in Germany Typesetting: Camera-ready by author, data conversion by Scientific Publishing Services, Chennai, India Printed on acid-free paper SPIN: 11363613 06/3142 543210
Preface: Toward an Integrated Study of Data Mining and Knowledge Management
Data mining (DM) and knowledge management (KM) are two important research areas, but with different emphases. Research and practice in these two areas have been largely conducted in parallel. The Chinese Academy of Sciences Symposium on Data Mining and Knowledge Management 2004 (CASDMKM 2004) held in Beijing, China (July 12–14, 2004) provided a unique opportunity for scholars to exchange ideas in these two areas. CASDMKM is a forum for discussing research findings and case studies in data mining, knowledge management and related fields such as machine learning and optimization problems. It promotes data mining technology, knowledge management tools and their real-life applications in the global economy. This volume of postsymposium proceedings contains 3 invited talks, as well as 25 papers selected from 60 original research papers submitted to the symposium. Contributions in this volume come from schol
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