Advances in Knowledge Discovery and Data Mining 11th Pacific-Asi
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Subseries of Lecture Notes in Computer Science
4426
Zhi-Hua Zhou Hang Li Qiang Yang (Eds.)
Advances in Knowledge Discovery and Data Mining 11th Pacific-Asia Conference, PAKDD 2007 Nanjing, China, May 22-25, 2007 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 Zhi-Hua Zhou Nanjing University National Lab for Novel Software Technology Hankou Road 22, Nanjing 210093, China E-mail: [email protected] Hang Li Microsoft Research Asia No. 49 Zhichun Road, Haidian District, Beijing, China 100080 E-mail: [email protected] Qiang Yang Hong Kong University of Science and Technology Department of Computer Science and Engineering Clearwater Bay, Kowloon, Hong Kong, China E-mail: [email protected]
Library of Congress Control Number: 2007923867
CR Subject Classification (1998): I.2, H.2.8, H.3, H.5.1, G.3, J.1, K.4 LNCS Sublibrary: SL 7 – Artificial Intelligence ISSN ISBN-10 ISBN-13
0302-9743 3-540-71700-5 Springer Berlin Heidelberg New York 978-3-540-71700-3 Springer Berlin Heidelberg New York
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Preface
The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) has been held every year since 1997. This year, the 11th in the series (PAKDD 2007), was held at Nanjing, China, May 22–25, 2007. PAKDD is a leading international conference in the area of data mining. It provides an international forum for researchers and industry practitioners to share their new ideas, original research results and practical development experiences from all KDD-related areas including data mining, machine learning, databases, statistics, data warehousing, data visualization, automatic scientific discovery, knowledge acquisition and knowledge-based systems. This year we received a record number of submissions. We received 730 research papers from 29 countries and regions in Asia, Australia, North America, South America, Europe and Africa. The submitted papers went through a rigorous reviewing process. Every submission except very few was reviewed by three reviewers. Moreover, for the first time, PAKDD 2007 introduced a procedure of having an area chai
