Machine Learning and Data Mining in Pattern Recognition

1. Front Matter

   Pages I-XI

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2. Invited Paper

   1. Technology of Text Mining

      • Ari Visa

      Pages 1-11

   2. Evaluation of Clinical Relevance of Clinical Laboratory Investigations by Data Mining

      • Ulrich Sack, Manja Kamprad

      Pages 12-22

3. Case-Based Reasoning and Associative Memory

   1. Temporal Abstractions and Case-Based Reasoning for Medical Course Data: Two Prognostic Applications

      • Rainer Schmidt, Lothar Gierl

      Pages 23-34

   2. Are Case-Based Reasoning and Dissimilarity-Based Classification Two Sides of the Same Coin?

      • Petra Perner

      Pages 35-51

   3. FAM-Based Fuzzy Inference for Detecting Shot Transitions

      • Seok-Woo Jang, Gye-Young Kim, Hyung-Il Choi

      Pages 52-61

4. Rule Induction and Grammars

   1. Rule-Based Ensemble Solutions for Regression

      • Nitin Indurkhya, Sholom M. Weiss

      Pages 62-72

   2. Learning XML Grammars

      • Henning Fernau

      Pages 73-87

   3. First-Order Rule Induction for the Recognition of Morphological Patterns in Topographic Maps

      • D. Malerba, F. Esposito, A. Lanza, F. A. Lisi

      Pages 88-101

5. Clustering and Conceptual Clustering

   1. Concepts Learning with Fuzzy Clustering and Relevance Feedback

      • Bir Bhanu, Anlei Dong

      Pages 102-116

   2. LC: A Conceptual Clustering Algorithm

      • José Fco. Martinez-Trinidad, Guillermo Sánchez-Diaz

      Pages 117-127

6. Data Mining on Signal, Images, Text and Temporal-Spatial Data

   1. Data Mining Approach Based on Information-Statistical Analysis: Application to Temporal-Spatial Data

      • Bon K. Sy, Arjun K. Gupta

      Pages 128-140

   2. A Hybrid Tool for Data Mining in Picture Archiving System

      • Petra Perner, Tatjana Belikova

      Pages 141-156

   3. Feature Selection for a Real-World Learning Task

      • D. Kollmar, D.H. Hellmann

      Pages 157-172

   4. Automatic Identification of Diatoms Using Decision Forests

      • Stefan Fischer, Horst Bunke

      Pages 173-183

   5. Validation of Text Clustering Based on Document Contents

      • Jarmo Toivonen, Ari Visa, Tomi Vesanen, Barbro Back, Hannu Vanharanta

      Pages 184-195

7. Nonlinear Function Learning and Neural Net Based Learning

   1. Statistical and Neural Approaches for Estimating Parameters of a Speckle Model Based on the Nakagami Distribution

      • Mark P. Wachowiak, Renata Smolíková, Mariofanna G. Milanova, Adel S. Elmaghraby

      Pages 196-205

   2. How to Automate Neural Net Based Learning

      • Roland Linder, Siegfried J. Pöppl

      Pages 206-216

   3. Nonlinear Function Learning and Classification Using Optimal Radial Basis Function Networks

      • Adam Krzyżak

      Pages 217-225

8. Learning for Handwriting Recognition

   1. Local Learning Framework for Recognition of Lowercase Handwritten Characters

      • Jian-xiong Dong, Adam Krzyżak, C. Y. Suen

      Pages 226-238

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.

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

• Institute of Computer Vision and Applied Computer Sciences, Leipzig, Germany

  Petra Perner

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