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《Science Technology and Engineering》 2009-07
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Research Multi-dimensional Association Rule Mining Based on Apriori Algorithm

SHENG Ying-ying,YAN Ren-wu,WANG Jia-min,LI Jia(School of Computer Science & Engineering,Jiangsu University of Science and Technology,Zhenjiang 212003,P.R.China)  
Association rules mining is very important in the application of data mining.Classic Apriori algorithm is one of the most influential association rules in mining boolean frequent itemsets algorithms,but is not suitable for mining multi-dimensional data model which rise in recent years.A "second cut" method is proposed,which is on the basis of the Apriori algorithm.The algorithm applies to multi-dimensional mining association rules,and to some extent improved the efficiency of the algorithm.
【CateGory Index】: TP311.13
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