Data Warehousing and Knowledge Discovery 9th International Conferenc
Data Warehousing and Knowledge Discovery have been widely accepted as key te- nologies for enterprises and organizations to improve their abilities in data analysis, decision support, and the automatic extraction of knowledge from data. With the exponenti
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Editorial Board David Hutchison Lancaster University, UK Takeo Kanade Carnegie Mellon University, Pittsburgh, PA, USA Josef Kittler University of Surrey, Guildford, UK Jon M. Kleinberg Cornell University, Ithaca, NY, USA Friedemann Mattern ETH Zurich, Switzerland John C. Mitchell Stanford University, CA, USA Moni Naor Weizmann Institute of Science, Rehovot, Israel Oscar Nierstrasz University of Bern, Switzerland C. Pandu Rangan Indian Institute of Technology, Madras, India Bernhard Steffen University of Dortmund, Germany Madhu Sudan Massachusetts Institute of Technology, MA, USA Demetri Terzopoulos University of California, Los Angeles, CA, USA Doug Tygar University of California, Berkeley, CA, USA Moshe Y. Vardi Rice University, Houston, TX, USA Gerhard Weikum Max-Planck Institute of Computer Science, Saarbruecken, Germany
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Il Yeal Song Johann Eder Tho Manh Nguyen (Eds.)
Data Warehousing and Knowledge Discovery 9th International Conference, DaWaK 2007 Regensburg Germany, September 3-7, 2007 Proceedings
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Volume Editors Il Yeal Song Drexel University College of Information Science and Technology Philadelphia, PA 19104, USA E-mail: [email protected] Johann Eder University of Vienna Faculty of Computer Science Dr.-Karl-Lueger-Ring 1, 1010 Wien, Austria E-mail: [email protected] Tho Manh Nguyen Vienna University of Technology Institute of Software Technology and Interactive Systems Favoriten Strasse 9-11/188, 1040 Wien, Austria E-mail: [email protected]
Library of Congress Control Number: 2007933373 CR Subject Classification (1998): H.2, H.3, H.4, C.2, H.2.8, H.5, I.2, J.1 LNCS Sublibrary: SL 3 – Information Systems and Application, incl. Internet/Web and HCI ISSN ISBN-10 ISBN-13
0302-9743 3-540-74552-1 Springer Berlin Heidelberg New York 978-3-540-74552-5 Springer Berlin Heidelberg New York
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Preface
Data Warehousing and Knowledge Discovery have been widely accepted as key technologies for enterprises and organizations to improve their abilities in data analysis, decision support, and the automatic extraction of knowledge from data. With the exponentially growing amount of information to be included in the decision-making process, the data
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