Post-mining: maintenance of association rules by wieghting

Authors:
Shichao Zhang;Chengqi Zhang;Xiaowei Yan
Affiliations:
Faculty of Information Technology, University of Technology, P.O. Box 123, Broadway NSW 2007, Sydney, Australia and School of Mathematics and Computing, Guangxi Teachers University, People's Repub ...;Faculty of Information Technology, University of Technology, P.O. Box 123, Broadway NSW 2007, Sydney, Australia;Faculty of Information Technology, University of Technology, P.O. Box 123, Broadway NSW 2007, Sydney, Australia
Venue:
Information Systems
Year:
2003

Citing 12
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Abstract

This paper proposes a new strategy for maintaining association rules in dynamic databases. This method uses weighting technique to highlight new data. Our approach is novel in that recently added transactions are given higher weights. In particular, we look at how frequent itemsets can be maintained incrementally. We propose a competitive model to 'promote' infrequent itemsets to frequent itemsets, and to 'degrade' frequent itemsets to infrequent itemsets incrementally. This competitive strategy can avoid retracing the whole data set. We have evalualed the proposed method. The experiments have shown that our approach is efficient and promising.