一种快速高效的关联规则挖掘算法

An Fast Adapted Algorithm for Mining Association Rules

本文提出了一种从大型数据库中挖掘关联规则的快速算法，该算法以经典的Apriori算法为基础，在分析研究各种优化算法的基础上．提出了自适应步长和扫描树的概念，并采用修剪的方法时Apnori算法进行了改进理论证明，它比Apriori算法的应用效率高，实验结果也证实了它的有效性。

This paper provides a fast algorithm for mining associating rules in large database,based on the traditional Aoriori and other optimal algorithm,reaserches the character of them.We not only develop the Adapted Step,but also improve the Apriori algorithm.The experimental results show that this algorithm is out performs Apriori.