Machine Learning and Data Mining in Pattern Recognition 5th Inte
MLDM / ICDM Medaillie Meissner Porcellan, the “White Gold” of King August the Strongest of Saxonia Gottfried Wilhelm von Leibniz, the great mathematician and son of Leipzig, was watching over us during our event in Machine Learning and Data Mining in Patt
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Subseries of Lecture Notes in Computer Science
4571
Petra Perner (Ed.)
Machine Learning and Data Mining in Pattern Recognition 5th International Conference, MLDM 2007 Leipzig, Germany, July 18-20, 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 Editor Petra Perner Institute of Computer Vision and Applied Computer Sciences (IBaI) Arno-Nitzsche-Str. 43, 04277 Leipzig, Germany E-mail: [email protected]
Library of Congress Control Number: 2007930460
CR Subject Classification (1998): I.2, I.5, I.4, F.4.1, H.3 LNCS Sublibrary: SL 7 – Artificial Intelligence ISSN ISBN-10 ISBN-13
0302-9743 3-540-73498-8 Springer Berlin Heidelberg New York 978-3-540-73498-7 Springer Berlin Heidelberg New York
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Preface
MLDM / ICDM Medaillie Meissner Porcellan, the “White Gold” of King August the Strongest of Saxonia
Gottfried Wilhelm von Leibniz, the great mathematician and son of Leipzig, was watching over us during our event in Machine Learning and Data Mining in Pattern Recognition (MLDM 2007). He can be proud of what we have achieved in this area so far. We had a great research program this year. This was the fifth MLDM in Pattern Recognition event held in Leipzig (www.mldm.de). Today, there are many international meetings carrying the title machine learning and data mining, whose topics are text mining, knowledge discovery, and applications. This meeting from the very first event has focused on aspects of machine learning and data mining in pattern recognition problems. We planned to reorganize classical and well-established pattern recognition paradigms from the view points of machine learning and data mining. Although it was a challenging program in the late 1990s, the idea has provided new starting points in pattern recognition and has influenced other areas such as cognitive computer vision. For this edition, the Program Committee received 258 submissions from 37 countries (see Fig. 1). To handle this high number of papers was a big challenge for the reviewers. Every paper was thoroughly reviewed and all authors received a detailed report o
