This book constitutes the thoroughly refereed joint postproceedings of the Third International Workshop on Knowledge Discovery in Inductive Databases, KDID 2004, held in Pisa, Italy in September 2004 in association with ECML/PKDD.
Inductive Databases support data mining and the knowledge discovery process in a natural way. In addition to usual data, an inductive database also contains inductive generalizations, like patterns and models extracted from the data. This book presents nine revised full papers selected from 23 submissions during two rounds of reviewing and improvement together with one invited paper. Various current topics in knowledge discovery and data mining in the framework of inductive databases are addressed.
Author(s): Sunita Sarawagi (auth.), Bart Goethals, Arno Siebes (eds.)
Series: Lecture Notes in Computer Science 3377 : Information Systems and Applications, incl. Internet/Web, and HCI
Edition: 1
Publisher: Springer-Verlag Berlin Heidelberg
Year: 2005
Language: English
Pages: 200
Tags: Database Management; Artificial Intelligence (incl. Robotics)
Front Matter....Pages -
Models and Indices for Integrating Unstructured Data with a Relational Database....Pages 1-10
Constraint Relaxations for Discovering Unknown Sequential Patterns....Pages 11-32
Mining Formal Concepts with a Bounded Number of Exceptions from Transactional Data....Pages 33-45
Theoretical Bounds on the Size of Condensed Representations....Pages 46-65
Mining Interesting XML-Enabled Association Rules with Templates....Pages 66-88
Database Transposition for Constrained (Closed) Pattern Mining....Pages 89-107
An Efficient Algorithm for Mining String Databases Under Constraints....Pages 108-129
An Automata Approach to Pattern Collections....Pages 130-149
Implicit Enumeration of Patterns....Pages 150-172
Condensed Representation of EPs and Patterns Quantified by Frequency-Based Measures....Pages 173-189
Back Matter....Pages -
