Mining dynamic association rules in databases

Authors:
Jinfeng Liu;Gang Rong
Affiliations:
National Key Laboratory of Industrial Control Technology, Zhejiang University, China;National Key Laboratory of Industrial Control Technology, Zhejiang University, China
Venue:
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Year:
2005

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Abstract

We put forward a new conception, dynamic association rule, which can describe the regularities of changes over time in association rules. The dynamic association rule is different in that it contains not only a support and a confidence but also a support vector and a confidence vector. During the mining process, the data used for mining is divided into several parts according to certain time indicators, such as years, seasons and months, and a support vector and a confidence vector for each rule are generated which show the support and the confidence of the rule in each subsets of the data. By using the two vectors, we can not only find the information about the rules’ changes with time but also predict the tendencies of the rules, which ordinary association rules can not offer.