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Machine Learning and Data Mining in Pattern Recognition

Petra Perner, Azriel Rosenfeld

Springer Verlag Berlin-Heidelberg 2003, ISBN: 3-540-40504-6,

Preface

Machine Learning and Data Mining in Pattern Recognition

The International Conference on Machine Learning and Data Mining (MLDM) is the third meeting in a series of biannual events which started in 1999, organized by the Institute of Computer Vision and Applied Computer Sciences (IBaI) in Leipzig. MLDM began as a workshop and is now a conference, and has brought the topic of machine learning and data mining to the attention of the research community.

Seventy-five papers were submitted to the conference this year. The program committee worked hard to select the most progressive research in a fair and competent review process which led to the acceptance of 33 papers for presentation at the conference.

The 33 papers in these Proceedings cover a wide variety of topics related to machine learning and data mining. The two invited talks deal with learning in case-based reasoning and with mining for structural data. The contributed papers can be grouped into nine areas: support vector machines; pattern discovery; decision trees; clustering; classification and retrieval; case-based reasoning; Bayesian models and methods; association rules; and applications.

We would like to express our appreciation to the reviewers for their precise and highly professional work. We are grateful to the German Science Foundation for their support of the Eastern European researchers. We appreciate the help and understanding of the editorial staff at Springer Verlag, and in particular Alfred Hofmann, who supported the publication of these proceedings in the LNAI series.

Last but not least, we wish to thank all the speakers and participants who contributed to the success of the conference.

Petra Perner, Azriel Rosenfeld