Knowledge Discovery in Inductive Databases 1st edition by Saso Dzeroski, Jan Struyf 3540755497, 9783540755494

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ISBN 10: 3540755497
ISBN 13: 9783540755494
Author: Saso Dzeroski, Jan Struyf

This book constitutes the thoroughly refereed joint postproceedings of the 5th International Workshop on Knowledge Discovery in Inductive Databases, KDID 2006, held in association with ECML/PKDD. Bringing together the fields of databases, machine learning, and data mining, the papers address various current topics in knowledge discovery and data mining in the framework of inductive databases such as constraint-based mining, database technology and inductive querying.

Knowledge Discovery in Inductive Databases 1st Table of contents:

1. Open Issues in Constrained Clustering
2. Mining Bisets in Numerical Data
3. Extending the Soft Constraint Based Mining Paradigm
4. On Interactive Pattern Mining from Relational Databases
5. Analysis of Time Series Data with Predictive Clustering Trees
6. Integrating Decision Tree Learning into Inductive Databases
7. Using a Reinforced Concept Lattice to Incrementally Mine Association Rules from Closed Itemsets
8. Initial Implementation and Early Results
9. Beam Search Induction and Similarity Constraints for Predictive Clustering Trees
10. Frequent Pattern Mining and Knowledge Indexing Based on ZeroSuppressed BDDs
11. Extracting Trees of Quantitative Serial Episodes
12. A Proposal for an Inductive Query Language
13. Mining Correct Properties in Incomplete Databases
14. Efficient Mining Under Rich Constraints Derived from Various Datasets
15. Three Strategies for Concurrent Processing of Frequent Itemset Queries Using FPGrowth
16. Towards a General Framework for Data Mining
17. Author Index

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