Title :
Dual-strategy Analysis Model Based on Clustering and Inter-transaction
Author :
Sun, Fan ; Ren, Yonggong ; Qi, Yanyan
Author_Institution :
Sch. of Comput. & Inf. Technol., Liaoning Normal Univ., Dalian, China
Abstract :
Inter-transactional association rules mining is mainly used in mining significant association between different transaction, but the existing algorithm only focus on the efficiency or accuracy. In this study, we propose the inter-transactional association rules algorithm based on cluster and dual-strategy analysis model. The algorithm adopts dual-strategy interest model to judge the integrity of the inter-transactional association rules, make up for mining bugs, avoid the generation of false rules, improve the quality of the mining algorithm; And use of cluster analysis to remove a large number of redundant data in database, improve the efficiency of the algorithm. The experimental results show that the proposed algorithm improves accuracy and efficiency of inter-transactional association rules algorithm.
Keywords :
Markov processes; data mining; database management systems; pattern clustering; transaction processing; cluster analysis; clustering model; database; dual-strategy analysis model; dual-strategy interest model; inter-transactional association rules mining; Algorithm design and analysis; Analytical models; Association rules; Clustering algorithms; Databases; Markov processes; Prediction algorithms;
Conference_Titel :
Web Information Systems and Applications Conference (WISA), 2011 Eighth
Conference_Location :
Chongqing
Print_ISBN :
978-1-4577-1812-0
DOI :
10.1109/WISA.2011.22