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

✍ Scribed by Kiri L. Wagstaff (auth.), Sašo Džeroski, Jan Struyf (eds.)

• Publisher: Springer-Verlag Berlin Heidelberg
• Year: 2007
• Tongue: English
• Leaves: 309
• Series: Lecture Notes in Computer Science 4747 : Information Systems and Applications, incl. Internet/Web, and HCI
• Edition: 1
• Category: Library

✦ Synopsis

This book constitutes the thoroughly refereed joint postproceedings of the 5th International Workshop on Knowledge Discovery in Inductive Databases, KDID 2006, held in Berlin, Germany, September 2006 in association with ECML/PKDD.

The 15 revised full papers presented together with one invited paper were carefully selected during two rounds of reviewing and improvement for inclusion in the book. 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.

✦ Table of Contents

Front Matter....Pages -
Value, Cost, and Sharing: Open Issues in Constrained Clustering....Pages 1-10
Mining Bi-sets in Numerical Data....Pages 11-23
Extending the Soft Constraint Based Mining Paradigm....Pages 24-41
On Interactive Pattern Mining from Relational Databases....Pages 42-62
Analysis of Time Series Data with Predictive Clustering Trees....Pages 63-80
Integrating Decision Tree Learning into Inductive Databases....Pages 81-96
Using a Reinforced Concept Lattice to Incrementally Mine Association Rules from Closed Itemsets....Pages 97-115
An Integrated Multi-task Inductive Database VINLEN: Initial Implementation and Early Results....Pages 116-133
Beam Search Induction and Similarity Constraints for Predictive Clustering Trees....Pages 134-151
Frequent Pattern Mining and Knowledge Indexing Based on Zero-Suppressed BDDs....Pages 152-169
Extracting Trees of Quantitative Serial Episodes....Pages 170-188
IQL: A Proposal for an Inductive Query Language....Pages 189-207
Mining Correct Properties in Incomplete Databases....Pages 208-222
Efficient Mining Under Rich Constraints Derived from Various Datasets....Pages 223-239
Three Strategies for Concurrent Processing of Frequent Itemset Queries Using FP-Growth....Pages 240-258
Towards a General Framework for Data Mining....Pages 259-300
Back Matter....Pages -

✦ Subjects

Database Management; Artificial Intelligence (incl. Robotics)