Knowledge Discovery in Inductive Databases: 4th International Workshop, KDID 2005, Porto, Portugal, October 3, 2005, Revised Selected and Invited Papers: 3933 (Lecture Notes in Computer Science, 3933) - Softcover

Softcover

ISBN 10: 3540332928 ISBN 13: 9783540332923

Publisher: Springer, 2006

Synopsis

The4thInternationalWorkshoponKnowledgeDiscoveryinInductiveDatabases (KDID 2005) was held in Porto, Portugal, on October 3, 2005 in conjunction with the 16th European Conference on Machine Learning and the 9th European Conference on Principles and Practice of Knowledge Discovery in Databases. Ever since the start of the ?eld of data mining, it has been realized that the integration of the database technology into knowledge discovery processes was a crucial issue. This vision has been formalized into the inductive database perspective introduced by T. Imielinski and H. Mannila (CACM 1996, 39(11)). The main idea is to consider knowledge discovery as an extended querying p- cess for which relevant query languages are to be speci?ed. Therefore, inductive databases might contain not only the usual data but also inductive gener- izations (e. g. , patterns, models) holding within the data. Despite many recent developments, there is still a pressing need to understand the central issues in inductive databases. Constraint-based mining has been identi?ed as a core technology for inductive querying, and promising results have been obtained for rather simple types of patterns (e. g. , itemsets, sequential patterns). However, constraint-based mining of models remains a quite open issue. Also, coupling schemes between the available database technology and inductive querying p- posals are not yet well understood. Finally, the de?nition of a general purpose inductive query language is still an on-going quest.

About this title

Synopsis

This book constitutes the thoroughly refereed joint post proceedings of the 4th International Workshop on Knowledge Discovery in Inductive Databases, KDID 2005, held in Porto, Portugal in October 2005 in association with ECML/PKDD.The 20 revised full papers presented together with 2 invited papers 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.

Edition details

• Publisher: Springer
• Publication date: 2006
• Language: English
• ISBN 10: 3540332928
• ISBN 13: 9783540332923
• Binding: Paperback
• Number of pages: 260
• Editor: Bonchi Francesco, Boulicaut Jean-Francois