Knowledge Discovery in Databases: PKDD 2006

1. Front Matter

   PDF

2. Invited Talks

   1. On Temporal Evolution in Data Streams

      • Charu C. Aggarwal

      Pages 1-1

   2. The Future of CiteSeer: CiteSeer x

      • C. Lee Giles

      Pages 2-2

   3. Learning to Have Fun

      • Jonathan Schaeffer

      Pages 3-3

   4. Winning the DARPA Grand Challenge

      • Sebastian Thrun

      Pages 4-4

   5. Challenges of Urban Sensing

      • Henry Tirri

      Pages 5-5

3. Long Papers

   1. SD-Map – A Fast Algorithm for Exhaustive Subgroup Discovery

      • Martin Atzmueller, Frank Puppe

      Pages 6-17

   2. Decision Trees for Hierarchical Multilabel Classification: A Case Study in Functional Genomics

      • Hendrik Blockeel, Leander Schietgat, Jan Struyf, Sašo Džeroski, Amanda Clare

      Pages 18-29

   3. Clustering Scientific Literature Using Sparse Citation Graph Analysis

      • Levent Bolelli, Seyda Ertekin, C. Lee Giles

      Pages 30-41

   4. VOGUE: A Novel Variable Order-Gap State Machine for Modeling Sequences

      • Bouchra Bouqata, Christopher D. Carothers, Boleslaw K. Szymanski, Mohammed J. Zaki

      Pages 42-54

   5. Don’t Be Afraid of Simpler Patterns

      • Björn Bringmann, Albrecht Zimmermann, Luc De Raedt, Siegfried Nijssen

      Pages 55-66

   6. An Adaptive Prequential Learning Framework for Bayesian Network Classifiers

      • Gladys Castillo, João Gama

      Pages 67-78

   7. Adaptive Active Classification of Cell Assay Images

      • Nicolas Cebron, Michael R. Berthold

      Pages 79-90

   8. Learning Parameters in Entity Relationship Graphs from Ranking Preferences

      • Soumen Chakrabarti, Alekh Agarwal

      Pages 91-102

   9. Detecting Fraudulent Personalities in Networks of Online Auctioneers

      • Duen Horng Chau, Shashank Pandit, Christos Faloutsos

      Pages 103-114

   10. Measuring Constraint-Set Utility for Partitional Clustering Algorithms

       • Ian Davidson, Kiri L. Wagstaff, Sugato Basu

       Pages 115-126

   11. Discovery of Interesting Regions in Spatial Data Sets Using Supervised Clustering

       • Christoph F. Eick, Banafsheh Vaezian, Dan Jiang, Jing Wang

       Pages 127-138

   12. Optimal String Mining Under Frequency Constraints

       • Johannes Fischer, Volker Heun, Stefan Kramer

       Pages 139-150

   13. k-Anonymous Decision Tree Induction

       • Arik Friedman, Assaf Schuster, Ran Wolff

       Pages 151-162

   14. Closed Sets for Labeled Data

       • Gemma C. Garriga, Petra Kralj, Nada Lavrač

       Pages 163-174

The two premier annual European conferences in the areas of machine learning anddatamining havebeencollocatedeversincethejointconferenceinFreiburg, Germany,2001. The European Conference on Machine Learning wasestablished 20 years ago, when the ?rst European Working Session on Learning was held in Orsay, France, in 1986. The conference is growing, and is more lively than ever. The European Conference on Principles and Practice of Knowledge Discovery in Databasescelebratesits tenth anniversary;the ?rst PKDD took place in 1997 in Trondheim, Norway. Over the years, the ECML/PKDD series has evolved into one of the largest and most selective international conferences in these areas, the only one that provides a common forum for the two closely related ?elds. In 2006, the 6th collocated ECML/PKDD took place during September 18-22, when the Humboldt-Universität zu Berlin hosted the 17th European Conference on Machine Learning (ECML) and the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD). The successful model of a hierarchical reviewing process that was introduced last year for the ECML/PKDD 2005 in Porto has been taken over in 2006. We nominated 32 Area Chairs, each of them responsible for several closely related research topics. Suitable areas were selected on the basis of the submission s- tistics for ECML/PKDD 2005 to ensure a proper load balance among the Area Chairs. For the ?rst time, a joint Program Committee was nominated for the two conferences, consisting of 280 renowned researchers,mostly proposed by the AreaChairs.

• algorithmic learning
• algorithms
• association rule mining
• classification
• cluster analysis
• data analysis
• data mining
• database
• decision trees
• knowledge discovery
• modeling
• pattern mining
• relational database
• sensing
• visualization

• Knowledge Engineering Group, Technische Universität Darmstadt,  

  Johannes Fürnkranz

• Max Planck Institute for Computer Science, Saarbrücken, Germany

  Tobias Scheffer

• Faculty of Computer Science, Otto-von-Guericke-University Magdeburg, Germany

  Myra Spiliopoulou