计算机科学 ›› 2016, Vol. 43 ›› Issue (1): 286-289.doi: 10.11896/j.issn.1002-137X.2016.01.061
张忠林,田苗凤,刘宗成
ZHANG Zhong-lin, TIAN Miao-feng and LIU Zong-cheng
摘要： 为满足大数据实时处理的需求,提出了一种基于划分的关联规则并行分层挖掘算法(Parallel Hierarchical Association Rule Mining,PHARM)。首先,将整个数据库D随机分割成若干个非重叠区域,并行挖掘出局部频繁项集；然后利用先验性质,连接局部频繁项集得全局候选项集；再次扫描D统计出每个候选项集的实际支持度,以确定全局频繁项集。最后,建模分析了该算法的高效性。
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