Title :
Variables Interaction for Mining Negative and Positive Quantitative Association Rules
Author :
Alachaher, Leila Nemmiche ; Guillaume, Sylvie
Author_Institution :
LIMOS, UBP UMR 6158 CNRS, Aubiere
Abstract :
This paper introduces an efficient method for mining both positive and negative quantitative association rules using a tabular pruning and regrouping strategy coordinated with an interestingness measure. This measure evaluates the impact of a new variable on the concerned association
Keywords :
data mining; data mining; negative quantitative association rule; positive quantitative association rule; regrouping strategy; tabular pruning; Artificial intelligence; Association rules; Coordinate measuring machines; Data mining; Itemsets; Transaction databases;
Conference_Titel :
Tools with Artificial Intelligence, 2006. ICTAI '06. 18th IEEE International Conference on
Conference_Location :
Arlington, VA
Print_ISBN :
0-7695-2728-0
DOI :
10.1109/ICTAI.2006.119
