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《Computer Engineering and Applications》 2002-11
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A Fast Algorithm for Mining of Association Rules

Du Xiaoping 1 Ma Xiuli 2 Tang Shiwei 1,2 Akifumi Makinouchi 31 (National Laboratory on Machine Perception,Center for Information Science ,Peking University,Beijing100871) 2 (Department of Computer Science&Technology,Peking University,Beijing1 00871) 3 (Gr  
Mining of association rules is considered to be on e of the most important data mining tasks.Frequent itemset mining plays an esse ntial role in mining association rules.A lot of previous studies adopt an Apri ori-like approach,in which hash-tree is used to store candidate itemsets base d on analyzing the bottleneck of performance for Apriori-like algorithm,an eff icient algorithm for faster mining of frequent itemsets is proposed in this pa per.It adopts one-dimension array instead of the complex hash-tree structure to expedite the mining process.The several experiments assess the relative perf ormance of the algorithm in comparison with the Apriori and its extended algorit hm.The experiment evaluation shows that the algorithm is faster than both alg orithms by a factor from two to five.
【Fund】: 国家973重点基础研究发展规划项目(编号:G1999032705);; 留学回国人员科研启动基金资助
【CateGory Index】: TP311.12
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