摘要
将FP-G rowth算法应用于面向目标的关联规则(OOA)挖掘,对FP-Tree的结点进行了修改,增加了目标支持度计数和效用度累计两个字段,对FP-G rowth算法进行了改进.实验结果表明,改进后的方法比基于Apriori算法和基于D free算法的OOA挖掘效率更高.
This paper applies FP-Growth algorithm to objective-oriented association rules （OOA） mining. For the sake of adaptability, FP-Growth algorithm is improved by modifying FP-tree＇s nodes and adding two fields of objective support counting and utility counting for each node. Experimental results show that the presented approach is more efficient than the algorithms based on Apriori or Disjunctive-free patterns.
出处
《集美大学学报（自然科学版）》
CAS
2006年第2期117-121,共5页
Journal of Jimei University：Natural Science
基金
福建省自然科学基金资助项目(A0310011)
福建省科技三项重点项目(K04005)
