Deriving strong association mining rules using a dependency criterion, the lift measure

Authors:
Sikha Bagui;Jiri Just;Subhash C. Bagui
Affiliations:
Department of Computer Science, University of West Florida, Pensacola, FL 32514, USA.;Department of Computer Science, University of West Florida, Pensacola, FL 32514, USA.;Department of Mathematics and Statistics, University of West Florida, Pensacola, FL 32514, USA
Venue:
International Journal of Data Analysis Techniques and Strategies
Year:
2009

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Abstract

Traditional association mining rule algorithms have two major drawbacks: first, there is a need to repeatedly scan the dataset and second, they generate too many association rules. In this paper, we have presented a dependency-based association mining rule algorithm, implemented using an array list structure in JAVA, that does not require more than one scan of the full dataset and generates a lot less strong association mining rules. The additional dependency criterion used was the lift measure.