关联规则挖掘Apriori算法的优化

Optimized Apriori Algorithm for Mining Association Rules

针对Apriori算法存在的不足,提出了一种新的优化Apriori的方法。该方法通过优化频繁项集修剪策略,减少无效候选项集的产生;优化连接策略,减少连接次数,避免相同项目的多次重复比较;结合事务数据库逐步压缩技术,减少对无用事务的扫描次数。实验结果表明,经过优化的Apriori算法具有更好的运行效率。

To address disadvantages of the Apriori algorithm,a new method is presented to optimize the Apriori.It can reduce the number of invalid candidate item sets through optimizing the strategy of frequent item sets pruning.In order to reduce the connections of items,avoid repeated comparison of the same items,it optimizes the joining strategy.And it also removes the useless transactions from database step by step in order to reduce the times of scanning transactions.The results of experiment show that the optimized algorithm is more efficient.