挖掘有效的关联规则

本文分析了关联规则的衡量标准，针对其中的缺点和不足，提出了一种匹配度方法用以取代置信度，并将该方法生成的规则与支持度一置信度框架生成的规则做了比较。结果表明，用本文方法生成的规则不仅前件和后件具有较高的相关性，而且减少了冗余规则的生成。

Mining Efficacious Association Rules

In this paper, we analyze the measure standard for association rules. In order to avoid the limitation in the criterion, we propose a new method of matching as the substitution of confidence. Experimental results show that there is higher correlation between the antecedent and the consequent of the rules produced by the improved method compared with the rules produced by the support-confidence framework. Furthermore, the improved method decreases the generation of redundancy rules.