Incremental maintenance of association rules based on multiple previously mined results

Authors:
Zhuohua Duan;Zixing Cai;Yan Lv
Affiliations:
Department of Computer, School of Information Engineering, Shaoguan University, Shaoguan, Guangdong, China;School of Information Science and Engineering, Central South University, Changsha, Hunan, China;School of Information Science and Engineering, Central South University, Changsha, Hunan, China
Venue:
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Year:
2006

Citing 3
Cited 0

Mining association rules between sets of items in large databases

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ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
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VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases

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Abstract

Incrementally maintaining association rules based on two or more classes of frequent item sets may reduce the costs of scanning the original database remarkably. However, it was considered as a method of saving time with more storage spaces. It is suggested in this paper that all frequent item sets of several minimal supports can be stored in a table with a little additional storage, and a representation model is given. Based on this model, the paper systematically discusses the problem of incremental maintenance based on discovered association rules of several minimal supports. Theoretical analysis and experiments show that the approach makes full use of the previous results and reduces the complexity of incremental maintenance algorithms.