A-Close+:一种挖掘频繁闭项集的算法

M. Shekofteh, A. M. Rahmani, M. A. Dezfuli
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引用次数: 1

摘要

关联规则挖掘(ARM)是挖掘大型数据库中数据之间隐藏关联的最基本技术。ARM最重要的功能是查找频繁项集。频繁闭项集(FCI)是一种重要的频繁项集压缩表示方法,由于其重要性,近年来出现了许多针对它的算法。频繁闭项集最基本的算法之一是A-close算法。在本文中,我们使用“减少剪枝时间”和“减少数据库大小”两种优化技术对该算法进行优化,称为“A-close+”。结果表明,该算法的性能代价明显小于A-close算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A-Close+: An Algorithm for Mining Frequent Closed Itemsets
Association Rule Mining (ARM) is the most essential technique for data mining that mines hidden associations between data in large databases. The most important function of ARM is to find frequent itemsets. Frequent closed itemsets (FCI) is an important condense representation method for frequent itemsets, and because of its importance in recent years, there have been many algorithms implemented for it. One of the most fundamental algorithms for frequent closed itemset is A-close. In this paper, we optimize this algorithm using both optimized techniques "reducing pruning time" and "reducing database size", called "A-close+"..Results show that the performance cost of our algorithm is considerably less than A-close.
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