摘要
Apriori算法是挖掘布尔关联规则频繁项集的最有影响的数据挖掘算法之一,但由于数据挖掘本身决定其面临的是海量数据,因此在许多情况下会产生大量候选项集,从而严重影响挖掘的效率。本文提出一种简单有效的Apriori改进算法。
Apriori algorithm is a classical algorithm of boolean association rule mining. However, data mining must consider the problem of discovering association rules between items in a large database of sales transactions. In most cases, it produces a great deal of candidates. We present a new algorithm for improving the efficiency of apriori algorithm.
出处
《长春理工大学学报（自然科学版）》
2007年第2期67-69,共3页
Journal of Changchun University of Science and Technology(Natural Science Edition)
