Machine Learning and Data Mining in Pattern Recognition 4th Internat
We met again in front of the statue of Gottfried Wilhelm von Leibniz in the city of Leipzig. Leibniz, a famous son of Leipzig, planned automatic logical inference using symbolic computation, aimed to collate all human knowledge. Today, artificial intellig
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Subseries of Lecture Notes in Computer Science
3587
Petra Perner Atsushi Imiya (Eds.)
Machine Learning and Data Mining in Pattern Recognition 4th International Conference, MLDM 2005 Leipzig, Germany, July 9-11, 2005 Proceedings
13
Series Editors Jaime G. Carbonell, Carnegie Mellon University, Pittsburgh, PA, USA Jörg Siekmann, University of Saarland, Saarbrücken, Germany Volume Editors Petra Perner Institute of Computer Vision and Applied Computer Sciences, IBaI Körnerstr 10, 04107 Leipzig, Germany E-mail: [email protected] Atsushi Imiya Chiba University, Department of Information and Image Sciences 1-33, Yayoi-cho, Inage-ku, Chiba-shi, Chiba, 263-8522, Japan E-mail: [email protected]
Library of Congress Control Number: 2005928444
CR Subject Classification (1998): I.2, I.5, I.4, F.4.1, H.3 ISSN ISBN-10 ISBN-13
0302-9743 3-540-26923-1 Springer Berlin Heidelberg New York 978-3-540-26923-6 Springer Berlin Heidelberg New York
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Preface
We met again in front of the statue of Gottfried Wilhelm von Leibniz in the city of Leipzig. Leibniz, a famous son of Leipzig, planned automatic logical inference using symbolic computation, aimed to collate all human knowledge. Today, artificial intelligence deals with large amounts of data and knowledge and finds new information using machine learning and data mining. Machine learning and data mining are irreplaceable subjects and tools for the theory of pattern recognition and in applications of pattern recognition such as bioinformatics and data retrieval. This was the fourth edition of MLDM in Pattern Recognition which is the main event of Technical Committee 17 of the International Association for Pattern Recognition; it started out as a workshop and continued as a conference in 2003. Today, there are many international meetings which are titled “machine learning” and “data mining”, whose topics are text mining, knowledge discovery, and applications. This meeting from the first 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 viewpoints of machine learning and data mini
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