KDID 2005: Porto, Portugal

Invited Papers

• Arno Siebes:
  Data Mining in Inductive Databases. 1-23
  
• Carlo Zaniolo:
  Mining Databases and Data Streams with Query Languages and Rules. 24-37
  

Contributed Papers

• Maurizio Atzori, Paolo Mancarella, Franco Turini:
  Memory-Aware Frequent k-Itemset Mining. 38-54
  
• Jérémy Besson, Ruggero G. Pensa, Céline Robardet, Jean-François Boulicaut:
  Constraint-Based Mining of Fault-Tolerant Patterns from Boolean Data. 55-71
  
• Hendrik Blockeel:
  Experiment Databases: A Novel Methodology for Experimental Research. 72-85
  
• Toon Calders, Bart Goethals:
  Quick Inclusion-Exclusion. 86-103
  
• Tao-Yuan Jen, Dominique Laurent, Nicolas Spyratos, Oumar Sy:
  Towards Mining Frequent Queries in Star Schemes. 104-123
  
• Stefan Kramer, Volker Aufschild, Andreas Hapfelmeier, Alexander Jarasch, Kristina Kessler, Stefan Reckow, Jörg Wicker, Lothar Richter:
  Inductive Databases in the Relational Model: The Data as the Bridge. 124-138
  
• Taneli Mielikäinen:
  Transaction Databases, Frequent Itemsets, and Their Condensed Representations. 139-164
  
• Siegfried Nijssen, Joost N. Kok:
  Multi-class Correlated Pattern Mining. 165-187
  
• Csaba István Sidló, András Lukács:
  Shaping SQL-Based Frequent Pattern Mining Algorithms. 188-201
  
• Arnaud Soulet, Bruno Crémilleux:
  Exploiting Virtual Patterns for Automatically Pruning the Search Space. 202-221
  
• Jan Struyf, Saso Dzeroski:
  Constraint Based Induction of Multi-objective Regression Trees. 222-233
  
• Bernard Zenko, Saso Dzeroski, Jan Struyf:
  Learning Predictive Clustering Rules. 234-250