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《Journal of Shaanxi University of Technology(Natural Science Edition)》 2018-05
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An improvement of Apriori algorithm based on association rules

ZHOU Kai;GU Hong-bo;LI Ai-guo;School of Computer and Information Technology,Northeast Petroleum University;Daqing Oilfield Engineer CO.;  
On the basis of the principles and steps of classic Apriori algorithm,aiming at the shortcoming of repeated database scanning of the Apriori algorithm,a fast algorithm for mining frequent itemsets is proposed. The algorithm forms a Boolean matrix corresponding to database by scanning the database at once.First,it judges whether the generated items belong to the frequent itemsets,then it can generate frequent itemsets quickly through the two ways of computing row vectors or column vectors of Boolean matrix. The experimental results show that the algorithm can ensure the accuracy of frequent itemsets and greatly shorten the time of producing frequent itemsets.
【Fund】: 黑龙江省自然科学基金资助项目(F2016002);; 东北石油大学科研基金资助项目(2017YDL-14)
【CateGory Index】: TP311.13
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