摘要
由于进行关联规则挖掘过程中会产生大量规则,给关联规则的后期分析与利用带来了巨大障碍。针对关联规则的特点,提出了一种新的规则相似性度量方法,通过相似性度量方法推出新的规则距离度量方法,运用系统聚类中的类平均法进行聚类。实验结果表明,该距离度量方法考虑了关联规则的整体信息,依据聚类谱系图和规则散点图,确定了类和类的个数,有利于规则的分类处理。
In the process of mining association rules,lots of rules are gotten,which bring great obstacles to analyze and utilize the association rules later.According to the characteristics of association rules,a new similarity measurement method is proposed in cluster analysis.The new distance approach is deduced by similarity measurement method.Then average method of hierarchical clustering is used to cluster rules.The results show that the new distance is useful for rules.The class and number of class is determined based on hierarchical diagram and rules plot,and in favor of classification of rules.
出处
《计算机工程与设计》
CSCD
北大核心
2012年第2期745-749,共5页
Computer Engineering and Design
基金
南昌航空大学校级教改课题基金项目(Jy0840)
关键词
关联规则
相似性
距离度量
系统聚类
分类
association rules
similarity
distance
hierarchical clustering
classification
