5. PKDD 2001: Freiburg, Germany
: Parametric Approximation Algorithms for High-Dimensional Euclidean Similarity.
: Pattern Extraction for Time Series Classification.
: Interestingness Measures for Fuzzy Association Rules.
: Discovery of Temporal Patterns. Learning Rules about the Qualitative Behaviour of Time Series.
, Osamu Konishi
: Temporal Rule Discovery for Time-Series Satellite Images and Integration with RDB.
: Biological Sequence Data Mining.
, Helge Ritter
: Text Categorization and Semantic Browsing with Self-Organizing Maps on Non-euclidean Spaces.
: Finding Association Rules That Trade Support Optimally against Confidence.
: Discovery of Temporal Knowledge in Medical Time-Series Databases Using Moving Average, Multiscale Matching, and Rule Induction.
: Mining Positive and Negative Knowledge in Clinical Databases Based on Rough Set Model.
: Combining Discrete Algorithmic and Probabilistic Approaches in Data Mining.
: Statistification or Mystification? The Need for Statistical Thought in Visual Data Mining.
: The Musical Expression Project: A Challenge for Machine Learning and Knowledge Discovery.
: Scalability, Search, and Sampling: From Smart Algorithms to Active Discovery.