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VLDB
1995
ACM

Discovery of Multiple-Level Association Rules from Large Databases

10 years 6 months ago
Discovery of Multiple-Level Association Rules from Large Databases
Previous studies on mining association rules find rules at single concept level, however, mining association rules at multiple concept levels may lead to the discovery of more specific and concrete knowledge from data. In this study, a top-down progressive deepening method is developed for mining multiplelevel association rules from large transaction databases by extension of some existing association rule mining techniques. A group of variant algorithms are proposed based on the ways of sharing intermediate results, with the relative performance tested on different kinds of data. Relaxation of the rule conditions for finding “level-crossing” association rules is also discussed in the paper.
Jiawei Han, Yongjian Fu
Added 26 Aug 2010
Updated 26 Aug 2010
Type Conference
Year 1995
Where VLDB
Authors Jiawei Han, Yongjian Fu
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