7. PKDD 2003: Cavtat-Dubrovnik, Croatia

@proceedings{DBLP:conf/pkdd/2003,
  editor    = {Nada Lavrac and
               Dragan Gamberger and
               Hendrik Blockeel and
               Ljupco Todorovski},
  title     = {Knowledge Discovery in Databases: PKDD 2003, 7th European Conference
               on Principles and Practice of Knowledge Discovery in Databases,
               Cavtat-Dubrovnik, Croatia, September 22-26, 2003, Proceedings},
  booktitle = {PKDD},
  publisher = {Springer},
  series    = {Lecture Notes in Computer Science},
  volume    = {2838},
  year      = {2003},
  isbn      = {3-540-20085-1},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Invited Papers

• Pieter W. Adriaans:
  From Knowledge-Based to Skill-Based Systems: Sailing as a Machine Learning Challenge. 1-8
  
• Leo Breiman:
  Two-Eyed Algorithms and Problems. 9
  
• Christos Faloutsos:
  Next Generation Data Mining Tools: Power Laws and Self-similarity for Graphs, Streams and Traditional Data. 10-15
  
• Donald B. Rubin:
  Taking Causality Seriously: Propensity Score Methodology Applied to Estimate the Effects of Marketing Interventions. 16-22
  

Contributed Papers

• Alan Ableson, Janice I. Glasgow:
  Efficient Statistical Pruning of Association Rules. 23-34
  
• Elena Baralis, Paolo Garza:
  Majority Classification by Means of Association Rules. 35-46
  
• Francesco Bonchi, Fosca Giannotti, Alessio Mazzanti, Dino Pedreschi:
  Adaptive Constraint Pushing in Frequent Pattern Mining. 47-58
  
• Francesco Bonchi, Fosca Giannotti, Alessio Mazzanti, Dino Pedreschi:
  ExAnte: Anticipated Data Reduction in Constrained Pattern Mining. 59-70
  
• Toon Calders, Bart Goethals:
  Minimal k-Free Representations of Frequent Sets. 71-82
  
• Gemma Casas-Garriga:
  Discovering Unbounded Episodes in Sequential Data. 83-94
  
• Michelangelo Ceci, Annalisa Appice, Donato Malerba:
  Mr-SBC: A Multi-relational Naïve Bayes Classifier. 95-106
  
• Nitesh V. Chawla, Aleksandar Lazarevic, Lawrence O. Hall, Kevin W. Bowyer:
  SMOTEBoost: Improving Prediction of the Minority Class in Boosting. 107-119
  
• Ludovic Denoyer, Patrick Gallinari:
  Using Belief Networks and Fisher Kernels for Structured Document Classification. 120-131
  
• Steven van Dijk, Linda C. van der Gaag, Dirk Thierens:
  A Skeleton-Based Approach to Learning Bayesian Networks from Data. 132-143
  
• Tapio Elomaa, Juho Rousu:
  On Decision Boundaries of Naïve Bayes in Continuous Domains. 144-155
  
• David P. Enot, Ross D. King:
  Application of Inductive Logic Programming to Structure-Based Drug Design. 156-167
  
• Eibe Frank, Mark Hall:
  Visualizing Class Probability Estimators. 168-179
  
• Jaana Heino, Hannu Toivonen:
  Automated Detection of Epidemics from the Usage Logs of a Physicians' Reference Database. 180-191
  
• Shoji Hirano, Shusaku Tsumoto:
  An Indiscernibility-Based Clustering Method with Iterative Refinement of Equivalence Relations. 192-203
  
• Stefan Holland, Martin Ester, Werner Kießling:
  Preference Mining: A Novel Approach on Mining User Preferences for Personalized Applications. 204-216
  
• Andreas Hotho, Steffen Staab, Gerd Stumme:
  Explaining Text Clustering Results Using Semantic Structures. 217-228
  
• Aleks Jakulin, Ivan Bratko:
  Analyzing Attribute Dependencies. 229-240
  
• Karin Kailing, Hans-Peter Kriegel, Peer Kröger, Stefanie Wanka:
  Ranking Interesting Subspaces for Clustering High Dimensional Data. 241-252
  
• Eamonn J. Keogh:
  Efficiently Finding Arbitrarily Scaled Patterns in Massive Time Series Databases. 253-265
  
• Michael Kockelkorn, Andreas Lüneburg, Tobias Scheffer:
  Using Transduction and Multi-view Learning to Answer Emails. 266-277
  
• Adam Kowalczyk, Bhavani Raskutti:
  Exploring Fringe Settings of SVMs for Classification. 278-290
  
• Antti Leino, Heikki Mannila, Ritva Liisa Pitkänen:
  Rule Discovery and Probabilistic Modeling for Onomastic Data. 291-302
  
• Marion Leleu, Christophe Rigotti, Jean-François Boulicaut, Guillaume Euvrard:
  Constraint-Based Mining of Sequential Patterns over Datasets with Consecutive Repetitions. 303-314
  
• Marcus-Christopher Ludl:
  Symbolic Distance Measurements Based on Characteristic Subspaces. 315-326
  
• Taneli Mielikäinen, Heikki Mannila:
  The Pattern Ordering Problem. 327-338
  
• Atsuyoshi Nakamura, Mineichi Kudo, Akira Tanaka:
  Collaborative Filtering Using Restoration Operators. 339-349
  
• Siegfried Nijssen, Joost N. Kok:
  Efficient Frequent Query Discovery in FARMER. 350-362
  
• Mordechai Nisenson, Ido Yariv, Ran El-Yaniv, Ron Meir:
  Towards Behaviometric Security Systems: Learning to Identify a Typist. 363-374
  
• Fei Pan, Baoying Wang, Yi Zhang, Dongmei Ren, Xin Hu, William Perrizo:
  Efficient Density Clustering Method for Spatial Data. 375-386
  
• Nam Hun Park, Won Suk Lee:
  Statistical sigma-Partition Clustering over Data Streams. 387-398
  
• Henri Prade, Gilles Richard, Mathieu Serrurier:
  Enriching Relational Learning with Fuzzy Predicates. 399-410
  
• Maximilien Sauban, Bernhard Pfahringer:
  Text Categorisation Using Document Profiling. 411-422
  
• Jouni K. Seppänen, Ella Bingham, Heikki Mannila:
  A Simple Algorithm for Topic Identification in 0-1 Data. 423-434
  
• Bernd Thomas:
  Bottom-Up Learning of Logic Programs for Information Extraction from Hypertext Documents. 435-446
  
• Luís Torgo, Rita Ribeiro:
  Predicting Outliers. 447-458
  
• Shusaku Tsumoto:
  Mining Rules of Multi-level Diagnostic Procedure from Databases. 459-470
  
• Teddy Turmeaux, Ansaf Salleb, Christel Vrain, Daniel Cassard:
  Learning Characteristic Rules Relying on Quantified Paths. 471-482
  
• Huaiyu Zhu, Shivakumar Vaithyanathan, Mahesh V. Joshi:
  Topic Learning from Few Examples. 483-494
  
• Djamel A. Zighed, Gilbert Ritschard, Walid Erray, Vasile-Marian Scuturici:
  Arbogodaï, a New Approach for Decision Trees. 495-506