基于BDIF的关联规则挖掘算法研究

On the Mining Algorithm Based on BDIF Association Rule

阐述了关联规则挖掘的研究情况,关联规则的分类方法等,对经典Apriori算法进行了分析和评价,在此基础上提出了一种高效产生频繁集的BDIF(Based Transactional Databases Including Frequent Item Set)算法;它通过划分数据块,快速的搜寻频繁项目集,从而减少对数据块的扫描次数,提高了算法的效率。并用Borland C++Builder6.0开发环境来调试、验证该算法。

This article describes research on association rule mining and classification methods of association rules, analyzes and evaluates the classic Apriori algorithm, which gives rise to an efficient frequent BDIF （Based Transactional Databases Including Frequent Item Set） algorithm. It thereby reduces scanning data block and improves algorithm efficiency by dividing data block and quickly searching for frequent item set.