Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/165

Mining inter-transaction associations with templates

Authors Feng, Ling
Lu, Hongjun
Yu, Jeffrey Xu
Han, Jiawei
Issue Date 1999
Source Proceedings of the Eighth International Conference on Information and Knowledge Management : CIKM '99, Kansas City, MI, USA, ACM, New York, USA , 2-6 Nov. 1999, p. 225-233
Summary 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.
Subjects
Rights © ACM, 1999. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Proceedings of the Eighth International Conference on Information and Knowledge Management : CIKM '99, Kansas City, MI, USA, 2-6 Nov. 1999, ACM, New York, USA, 1999, p. 225-233
Language English
Format Conference paper
Access
Files in this item:
File Description Size Format
cikm99_lu.pdf 314244 B Adobe PDF