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An Efficient Hash-Based Algorithm for Mining Frequent Closed Itemsets

机译:基于高效的散列算法频繁关闭项目集

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The frequent itemsets are the main step in the association rule mining, frequent closed itemset tend to be a condensed representation method for frequent itemsets which have smaller set but carry the power similar to the frequent itemsets, and remove redundant rules. This study employs hashing technique to improve one of the most basic algorithms used in this area. The results of the implementation of the new algorithm shows that it is more efficient as far as execution time is concerned.
机译:频繁的项目集是关联规则挖掘中的主要步骤,频繁关闭的项目集倾向于是频繁的项目集的浓缩表示方法,该方法具有较小的集合,而携带类似于频繁项集的权力,并删除冗余规则。本研究采用散列技术来改进该区域中使用的最基本算法之一。新算法实现的结果表明,只要执行时间就会更有效。

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