Outcome of a Dagstuhl Seminar: Local Pattern Detection 2004

• Francesco Bonchi, Fosca Giannotti:
  Pushing Constraints to Detect Local Patterns. 1-19
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• Johannes Fürnkranz:
  From Local to Global Patterns: Evaluation Issues in Rule Learning Algorithms. 20-38
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• David J. Hand, Niall M. Adams, Nick A. Heard:
  Pattern Discovery Tools for Detecting Cheating in Student Coursework. 39-52
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• Frank Höppner:
  Local Pattern Detection and Clustering. 53-70
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• Nada Lavrac, Filip Zelezný, Saso Dzeroski:
  Local Patterns: Theory and Practice of Constraint-Based Relational Subgroup Discovery. 71-88
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• Dunja Mladenic, Marko Grobelnik:
  Visualizing Very Large Graphs Using Clustering Neighborhoods. 89-97
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• Katharina Morik, Hanna Köpcke:
  Features for Learning Local Patterns in Time-Stamped Data. 98-114
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• Ruggero G. Pensa, Jean-François Boulicaut:
  Boolean Property Encoding for Local Set Pattern Discovery: An Application to Gene Expression Data Analysis. 115-134
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• Céline Rouveirol, François Radvanyi:
  Local Pattern Discovery in Array-CGH Data. 135-152
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• Stefan Rüping:
  Learning with Local Models. 153-170
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• Martin Scholz:
  Knowledge-Based Sampling for Subgroup Discovery. 171-189
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• Myra Spiliopoulou, Steffan Baron:
  Temporal Evolution and Local Patterns. 190-206
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• Einoshin Suzuki:
  Undirected Exception Rule Discovery as Local Pattern Detection. 207-216
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• Claus Weihs, Uwe Ligges:
  From Local to Global Analysis of Music Time Series. 217-231
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