Contents

Highlights

• Applications of Data Mining/Machine Learning in
• Environmental Sciences
• Life Sciences
• Natural Language Processing
• Combining Classifiers and Meta-Learning
• Computational Scientific Discovery and Equation Discovery
• Constraint-Based Data Mining and Data Mining Query Laguages
• Inductive Databases and Inductive Queries
• Inductive Logic Programming and Relational Data Mining

• IQ: Inductive Queries for Mining Patterns and Models
• SIGMEA: Sustainable Introduction of GMOs into European Agriculture
• ECOGEN: Soil ecological and economic evaluation of genetically modified crops
• cInQ: consortium on discovering knowledge with Inductive Queries
• METAL: A Meta-Learning Assistant for Providing User Support in Machine Learning and Data Mining
• ILPnet2: Network of Excellence in Inductive Logic Programming

• Learning in rich representations: Inductive logic programming and computational scientific discovery. ICML-2002. In Proc. Nineteenth International Conference on Machine Learning. ILP-2002. In Proc. Twelfth International Conference on Inductive Logic Programming.
  Sydney, Australia, July 2002.
• Relational reinforcement learning for agents in worlds with objects. AAMAS-2. In Proc. AISB Symposium on Adaptive Agents and Multi-Agent Systems. London, UK, April 2002.
• Computational scientific discovery and inductive databases. AM-2002. In Proc. ICDM International Workshop on Active Mining. Maebashi City, Japan, December 2002.

• Multi-Relational Data Mining (S. Dzeroski and L. De Raedt). KDD-2003. Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Washington DC, USA, August 2003.
• Relational Data Mining. SDM-2003. SIAM International Conference on Data Mining. San Francisco, USA, May 2003.
• Relational Data Mining. IEEE International Conference on Data Mining. Maebashi City, Japan, December 2002.

• Computational Discovery of Communicable Knowledge
• Relational Data Mining
• Learning Language in Logic
• Inductive Logic Programming: Techniques and Applications

• SIGKDD Explorations, 5(1), 2003. Special Issue on Multi-Relational Data Mining.
• Machine learning, 44(3), 2001. Special Issue on Inductive Logic Programming.
• Data Mining and Knowledge Discovery, 3(1), 1999. Special Issue on Inductive Logic Programming.
• New Generation Computing, 17(1), 1999. Special Issue on Inductive Logic Programming.

• Machine Learning Journal
• Journal of Artificial Intelligence Research
• Journal of Machine Learning Research
• Data Mining and Knowledge Discovery Journal

• Program chair:
  • AEDML-2004. Analysis of environmental data with machine learning methods.
    Ljubljana, Slovenia, October 2004. Program chair.
    
  • EAML-2004. International Workshop on Environmental Applications of Machine Learning and Data Mining.
    Bled, Slovenia, September 2004. Program co-chair with B. Zenko.
    
  • ECEM-2004. Fourth European Conference on Ecological Modelling.
    Bled, Slovenia, September 2004. Program co-chair with M. Debeljak.
• Publicity co-chair:
  • SDM-2004
• Program committee member:
  • ICML-2004
  • ECML/PKDD-2004
  • DS-2004
  • DaWaK-2004
  • AAMAS-2004
  • PaRMa-2004

• Conferences:
  • ICML-99. Sixteenth International Conference on Machine Learning.
    Bled, Slovenia, June 1999. Co-chair with I. Bratko.
    
  • ILP-99. Ninth International Workshop on Inductive Logic Programming.
    Bled, Slovenia, June 1999. Co-chair with P. Flach.
    
  • ILP-97. Seventh International Workshop on Inductive Logic Programming.
    Prague, Czech Republic, September 1997. Program co-chair with N. Lavrac.
• Workshops:
  • KDID-03. Workshop on Knowledge Discovery in Inductive Databases held at ECML/PKDD-2003. Cavtat-Dubrovnik, Croatia, September, 2003. Co-chair with J.-F. Boulicaut.
    
  • MRDM-03. Workshop on Multi-Relational Data Mining in conjunction with KDD-2003. Washington, DC, USA, August 2003. Co-chair with L. De Raedt and S. Wrobel.
    
  • MRDM-02. Workshop on Multi-Relational Data Mining in conjunction with KDD-2002. Edmonton, Canada, July 2002. Co-chair with L. De Raedt and S. Wrobel.
• Summer schools:
  • Summer School on Relational Data Mining
  • Inductive Logic Programming Tutorial Day
  • Summer School on Inductive Logic Programming and Knowledge Discovery in Databases
• Seminars:
  • Analysis of environmental data with machine learning methods.