Efficient mining of constrained correlated sets
- 7 November 2002
- proceedings article
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 512-521
- https://doi.org/10.1109/icde.2000.839450
Abstract
In this paper, we study the problem of efficiently computing correlated itemsets satisfying given constraints. We call them valid correlated itemsets. It turns out constraints can have subtle interactions with correlated itemsets, depending on their underlying properties. We show that in general the set of minimal valid correlated itemsets does not coincide with that of minimal correlated itemsets that are valid, and characterize classes of constraints for which these sets coincide. We delineate the meaning of these two spaces and give algorithms for computing them. We also give an analytical evaluation of their performance and validate our analysis with a detailed experimental evaluation.Keywords
This publication has 15 references indexed in Scilit:
- Mining sequential patternsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Integrating association rule mining with relational database systemsPublished by Association for Computing Machinery (ACM) ,1998
- Exploratory mining and pruning optimizations of constrained associations rulesPublished by Association for Computing Machinery (ACM) ,1998
- Database systems—breaking out of the boxACM SIGMOD Record, 1997
- Levelwise Search and Borders of Theories in Knowledge DiscoveryData Mining and Knowledge Discovery, 1997
- Beyond market basketsPublished by Association for Computing Machinery (ACM) ,1997
- An effective hash-based algorithm for mining association rulesPublished by Association for Computing Machinery (ACM) ,1995
- Efficient parallel data mining for association rulesPublished by Association for Computing Machinery (ACM) ,1995
- Finding interesting rules from large sets of discovered association rulesPublished by Association for Computing Machinery (ACM) ,1994
- Improved Decision Trees: A Generalized Version of ID3Published by Elsevier ,1988