一种挖掘统计显著频繁项集的有效方法

Publications De L'institut Mathematique Pub Date : 1900-01-01 DOI:10.2298/PIM1001109S

P. Stanisic, S. Tomovic

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引用次数: 0

摘要

我们提出了原始的频繁项集生成过程，该过程比已知的Apriori算法的适当过程更有效。该程序的正确性是基于一个特殊的结构，称为赖蒙树。对于其实现，我们提出了一种改进的排序-合并-连接算法。最后，我们解释了在Apriori算法中使用的支持度量如何给出统计显著的频繁项集。

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An efficient procedure for mining statistically significant frequent itemsets

We suggest the original procedure for frequent itemsets generation, which is more efficient than the appropriate procedure of the well known Apriori algorithm. The correctness of the procedure is based on a special structure called Rymon tree. For its implementation, we suggest a modified sort-merge-join algorithm. Finally, we explain how the support measure, which is used in Apriori algorithm, gives statistically significant frequent itemsets.

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Publications De L'institut Mathematique

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