Apriori算法中频繁项集挖掘实现研究

Realization of Mining Frequent Itemsets Based on Apriori

在数据挖掘中,关联规则是发现知识的一种有效方法,而频繁项集的挖掘是关联规则中发现强规则的基础,其中连接与剪枝是逐层迭代求解k-项频繁集的核心算法。因此,文中主要介绍了基于连接与剪枝挖掘频繁项集的实现过程,并通过挖掘对传统购物篮数据中的频繁项集进行了验证,结果是一致的。算法的有效性也为进一步挖掘关联规则中的强规则提供了基础。

It is a very efficient tool to find useful knowledge from database by using association rules. In order to find strong rules, it needs to mining frequent itemsets based on Apriori. The algorithms of linking and pruning are building up candidate （ k ＋ 1） - itemsets from k - itemsets recursive in sequenee. The realization of mining frequent itemsets based on linking algorithm and pruning algorithm is introduced in this paper. Through an example, perform validation to discover the frequent itemsets from traditional shopping basket. The strong rules are easily found by the algorithms.