Advanced Data Mining and Applications Second International Confe
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Xue Li Osmar R. Zaïane Zhanhuai Li (Eds.)
Advanced Data Mining and Applications Second International Conference, ADMA 2006 Xi’an, China, August 2006 Proceedings
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Lecture Notes in Artificial Intelligence Edited by J. G. Carbonell and J. Siekmann
Subseries of Lecture Notes in Computer Science
4093
Xue Li Osmar R. Zaïane Zhanhuai Li (Eds.)
Advanced Data Mining and Applications Second International Conference, ADMA 2006 Xi’an, China, August 14-16, 2006 Proceedings
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Series Editors Jaime G. Carbonell, Carnegie Mellon University, Pittsburgh, PA, USA Jörg Siekmann, University of Saarland, Saarbrücken, Germany Volume Editors Xue Li The University of Queensland School of Information Technology and Electronic Engineering Queensland, Australia E-mail: [email protected] Osmar R. Zaïane University of Alberta, Canada E-mail: [email protected] Zhanhuai Li Northwest Polytechnical University, China E-mail: [email protected]
Library of Congress Control Number: 2006930269
CR Subject Classification (1998): I.2, H.2.8, H.3-4, K.4.4, J.3, I.4, J.1 LNCS Sublibrary: SL 7 – Artificial Intelligence ISSN ISBN-10 ISBN-13
0302-9743 3-540-37025-0 Springer Berlin Heidelberg New York 978-3-540-37025-3 Springer Berlin Heidelberg New York
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Preface
The Second International Conference on Advanced Data Mining and Applications (ADMA) aimed at establishing its identity in the research community. The theme of ADMA is to focus on the innovative applications of data mining approaches to real-world problems that involve large data sets, incomplete and noisy data, or demand optimal solutions. Data mining is essentially a problem involving different knowledge of data, algorithms, and application domains. The first is about data that are regarded as the “first-class citizens” in application system development. Understanding data is always critical: their structures, high dimensionality, and their qualification and quantification issues. The second is about algorithms: their effectiveness, efficiency, scalability, and their applicability. Amongst a variety of applicable algorithms, selecting a right one to deal with a specific problem is always a challenge that demands contributions from t
