概念层次架构的挖掘关联规则及其实证应用  

A mining association rule based on conceptual hierarchy and its applications

作　　者：王建骅 陈兆芳 郑莉 

机构地区：[1]福建工程学院管理学院,福建福州350118

出　　处：《福建工程学院学报》2017年第6期597-605,共9页Journal of Fujian University of Technology

基　　金：福建工程学院教育科学研究项目(GB-K-17-31)

摘　　要：在概念层次里进行关联规则的挖掘,并考虑到用户感知与主观判断所产生的认知不确定性;结合模糊分割法与FP-Growth方法,应用于概念层次架构中找出关联规则方法,主要分为两个阶段:层级架构的顺序将数据项做抽象化,找出高频模糊格;由高频模糊格来产生多层次模糊关规则。最后通过比较验证所提方法可提高算法的执行效率、缩短计算时间。An association rule was explored on the conceptual hierarchy and the cognitive uncertainty caused by users＇ perception and subjective judgment was considered. The fuzzy partition method and FP-Growth were combined to mine the association rules on the conceptual hierarchy. It mainly consisted of two phases ： the first was to find the high frequency fuzzy patterns by abstracting data items in the order of the hierarchical structure and the second was to generate multiple-level fuzzy association rules from those frequent patterns. Experiments and comparisons with other methods show that the proposed method could improve the efficiency of the algorithm and shorten the computational time.

关 键 词：数据挖掘 模糊分割法 FP-GROWTH 关联规则 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]