Mining inter-transaction associations with templates

Authors:
Ling Feng;Hongjun Lu;Jeffrey Xu Yu;Jiawei Han
Affiliations:
Hong Kong Polytechnic University, China;Hong Kong University of Science and Technology, China;Australian National University, Australia;Simon Fraser University, Canada
Venue:
Proceedings of the eighth international conference on Information and knowledge management
Year:
1999

Citing 7
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Abstract

Multi-dimensional, inter-transaction association rules extend the traditional association rules to describe more general associations among items with multiple properties cross transactions. “After McDonald and Burger King open branches, KFC will open a branch two months later and one mile away” is an example of such rules. Since the number of potential inter-transaction association rules tends to be extremely large, mining inter-transaction associations poses more challenges on efficient processing than mining intra-transaction associations. In order to make such association mining truly practical and computationally tractable, in this study, we present a template model to help users declare the interesting inter-transaction associations to be mined. With the guidance of templates, several optimization techniques are devised to speed up the discovery of inter-transaction association rules. We show, through a series of experiments, that these optimization techniques can yield significant performance benefits.