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KDID 2005: Porto, Portugal
- Francesco Bonchi, Jean-François Boulicaut:
Knowledge Discovery in Inductive Databases, 4th International Workshop, KDID 2005, Porto, Portugal, October 3, 2005, Revised Selected and Invited Papers. Lecture Notes in Computer Science 3933, Springer 2006, ISBN 3-540-33292-8
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
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
Learning Predictive Clustering Rules. 234-250
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