Knowledge Discovery in Databases: PKDD 2003

1. Front Matter

   PDF

2. Invited Papers

   1. From Knowledge-Based to Skill-Based Systems: Sailing as a Machine Learning Challenge

      • Pieter Adriaans

      Pages 1-8

   2. Two-Eyed Algorithms and Problems

      • Leo Breiman

      Pages 9-9

   3. Next Generation Data Mining Tools: Power Laws and Self-similarity for Graphs, Streams and Traditional Data

      • Christos Faloutsos

      Pages 10-15

   4. Taking Causality Seriously: Propensity Score Methodology Applied to Estimate the Effects of Marketing Interventions

      • Donald B. Rubin

      Pages 16-22

3. Contributed Papers

   1. Efficient Statistical Pruning of Association Rules

      • Alan Ableson, Janice Glasgow

      Pages 23-34

   2. Majority Classification by Means of Association Rules

      • Elena Baralis, Paolo Garza

      Pages 35-46

   3. Adaptive Constraint Pushing in Frequent Pattern Mining

      • Francesco Bonchi, Fosca Giannotti, Alessio Mazzanti, Dino Pedreschi

      Pages 47-58

   4. ExAnte: Anticipated Data Reduction in Constrained Pattern Mining

      • Francesco Bonchi, Fosca Giannotti, Alessio Mazzanti, Dino Pedreschi

      Pages 59-70

   5. Minimal k-Free Representations of Frequent Sets

      • Toon Calders, Bart Goethals

      Pages 71-82

   6. Discovering Unbounded Episodes in Sequential Data

      • Gemma Casas-Garriga

      Pages 83-94

   7. Mr-SBC: A Multi-relational Naïve Bayes Classifier

      • Michelangelo Ceci, Annalisa Appice, Donato Malerba

      Pages 95-106

   8. SMOTEBoost: Improving Prediction of the Minority Class in Boosting

      • Nitesh V. Chawla, Aleksandar Lazarevic, Lawrence O. Hall, Kevin W. Bowyer

      Pages 107-119

   9. Using Belief Networks and Fisher Kernels for Structured Document Classification

      • Ludovic Denoyer, Patrick Gallinari

      Pages 120-131

   10. A Skeleton-Based Approach to Learning Bayesian Networks from Data

       • Steven van Dijk, Linda C. van der Gaag, Dirk Thierens

       Pages 132-143

   11. On Decision Boundaries of Naïve Bayes in Continuous Domains

       • Tapio Elomaa, Juho Rousu

       Pages 144-155

   12. Application of Inductive Logic Programming to Structure-Based Drug Design

       • David P. Enot, Ross D. King

       Pages 156-167

   13. Visualizing Class Probability Estimators

       • Eibe Frank, Mark Hall

       Pages 168-179

   14. Automated Detection of Epidemics from the Usage Logs of a Physicians’ Reference Database

       • Jaana Heino, Hannu Toivonen

       Pages 180-191

   15. An Indiscernibility-Based Clustering Method with Iterative Refinement of Equivalence Relations

       • Shoji Hirano, Shusaku Tsumoto

       Pages 192-203

The proceedings of ECML/PKDD2003 are published in two volumes: the P- ceedings of the 14th European Conference on Machine Learning (LNAI 2837) and the Proceedings of the 7th European Conference on Principles and Practice of Knowledge Discovery in Databases (LNAI 2838). The two conferences were held on September 22–26, 2003 in Cavtat, a small tourist town in the vicinity of Dubrovnik, Croatia. As machine learning and knowledge discovery are two highly related ?elds, theco-locationofbothconferencesisbene?cialforbothresearchcommunities.In Cavtat, ECML and PKDD were co-located for the third time in a row, following the successful co-location of the two European conferences in Freiburg (2001) and Helsinki (2002). The co-location of ECML2003 and PKDD2003 resulted in a joint program for the two conferences, including paper presentations, invited talks, tutorials, and workshops. Out of 332 submitted papers, 40 were accepted for publication in the ECML2003proceedings,and40wereacceptedforpublicationinthePKDD2003 proceedings. All the submitted papers were reviewed by three referees. In ad- tion to submitted papers, the conference program consisted of four invited talks, four tutorials, seven workshops, two tutorials combined with a workshop, and a discovery challenge.

• Bayesian network
• classification
• data mining
• database
• knowledge discovery
• learning
• logic
• pattern mining
• programming

• University of Nova Gorica, Nova Gorica, Slovenia

  Nada Lavrač

• Rudjer Bošković Institute, Zagreb, Croatia

  Dragan Gamberger

• Jozef Stefan Institute, Ljubljana, Slovenia

  Ljupčo Todorovski

• Leiden Institute of Advanced Computer Science, Leiden University,  

  Hendrik Blockeel

 

This book constitutes the refereed proceedings of the 7th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2003, held in Cavtat-Dubrovnik, Croatia in September 2003 in conjunction with ECML 2003.

The 40 revised full papers presented together with 4 invited contributions were carefully reviewed and, together with another 40 ones for ECML 2003, selected from a total of 332 submissions. The papers address all current issues in data mining and knowledge discovery in databases including data mining tools, association rule mining, classification, clustering, pattern mining, multi-relational classifiers, boosting, kernel methods, learning Bayesian networks, inductive logic programming, user preferences mining, time series analysis, multi-view learning, support vector machine, pattern mining, relational learning, categorization, information extraction, decision making, prediction, and decision trees.

Policies and ethics