Machine Learning and Data Mining in Pattern Recognition

Second International Workshop, MLDM 2001 Leipzig, Germany, July 25–27, 2001 Proceedings

  • Petra Perner
Conference proceedings MLDM 2001

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2123)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 2123)

Table of contents

  1. Front Matter
    Pages I-XI
  2. Invited Paper

  3. Case-Based Reasoning and Associative Memory

  4. Rule Induction and Grammars

    1. Nitin Indurkhya, Sholom M. Weiss
      Pages 62-72
    2. Henning Fernau
      Pages 73-87
  5. Clustering and Conceptual Clustering

    1. José Fco. Martinez-Trinidad, Guillermo Sánchez-Diaz
      Pages 117-127
  6. Data Mining on Signal, Images, Text and Temporal-Spatial Data

    1. Petra Perner, Tatjana Belikova
      Pages 141-156
    2. D. Kollmar, D.H. Hellmann
      Pages 157-172
    3. Stefan Fischer, Horst Bunke
      Pages 173-183
    4. Jarmo Toivonen, Ari Visa, Tomi Vesanen, Barbro Back, Hannu Vanharanta
      Pages 184-195
  7. Nonlinear Function Learning and Neural Net Based Learning

    1. Mark P. Wachowiak, Renata Smolíková, Mariofanna G. Milanova, Adel S. Elmaghraby
      Pages 196-205
    2. Roland Linder, Siegfried J. Pöppl
      Pages 206-216
  8. Learning for Handwriting Recognition

    1. Jian-xiong Dong, Adam Krzyżak, C. Y. Suen
      Pages 226-238

About these proceedings

Introduction

This book constitutes the refereed proceedings of the Second International Workshop on Machine Learning and Data Mining in Pattern Recognition, MLDM 2001, held in Leipzig, Germany in July 2001.
The 26 revised full papers presented together with two invited papers were carefully reviewed and selected for inclusion in the proceedings. The papers are organized in topical sections on case-based reasoning and associative memory; rule induction and grammars; clustering and conceptual clustering; data mining on signals, images, and spatio-temporal data; nonlinear function learning and neural net based learning; learning for handwriting recognition; statistical and evolutionary learning; and content-based image retrieval.

Keywords

Algorithmic Learning Classification Clustering Data Mining Handwriting Recognition Information Retrieval Machine Learning Object Recognition Statistical Learning Text Mining case-based reasoning learning pattern recognition

Editors and affiliations

  • Petra Perner
    • 1
  1. 1.Institute of Computer Vision and Applied Computer SciencesLeipzigGermany

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-44596-X
  • Copyright Information Springer-Verlag Berlin Heidelberg 2001
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-42359-1
  • Online ISBN 978-3-540-44596-8
  • Series Print ISSN 0302-9743
  • About this book