Knowledge Discovery in Inductive Databases 5th International Workshop, KDID 2006 Berlin, Germany, September 18th, 2006 Revised Selected and Invited Papers

Invited Talk.- Value, Cost, and Sharing: Open Issues in Constrained Clustering.- Contributed Papers.- Mining Bi-sets in Numerical Data.- Extending the Soft Constraint Based Mining Paradigm.- On Interactive Pattern Mining from Relational Databases.- Analysis of Time Series Data with Predictive Clustering Trees.- Integrating Decision Tree Learning into Inductive Databases.- Using a Reinforced Concept Lattice to Incrementally Mine Association Rules from Closed Itemsets.- An Integrated Multi-task Inductive Database VINLEN: Initial Implementation and Early Results.- Beam Search Induction and Similarity Constraints for Predictive Clustering Trees.- Frequent Pattern Mining and Knowledge Indexing Based on Zero-Suppressed BDDs.- Extracting Trees of Quantitative Serial Episodes.- IQL: A Proposal for an Inductive Query Language.- Mining Correct Properties in Incomplete Databases.- Efficient Mining Under Rich Constraints Derived from Various Datasets.- Three Strategies for Concurrent Processing of Frequent Itemset Queries Using FP-Growth.- Discussion Paper.- Towards a General Framework for Data Mining.