基于FP_Growth算法的关联规则挖掘研究及应用  

Research and Application of Association Rule Mining Based on FP_Growth Algorithm

作　　者：马瑞敏[1] 吴海霞[1] MA Ruimin;WU Haixia(Department of Computer Science,Changzhi University,Changzhi 046011,China)

机构地区：[1]长治学院计算机系,山西长治046011

出　　处：《太原师范学院学报（自然科学版）》2021年第1期19-22,共4页Journal of Taiyuan Normal University:Natural Science Edition

基　　金：2020年山西省高等学校创新创业计划项目(2020600).

摘　　要：关联规则的发现对于挖掘数据中的隐含信息非常重要,针对关联规则挖掘算法进行研究,分析了利用FP_Growth算法构建FP-tree和递归挖掘频繁项集的过程,并应用该算法对大学生兴趣爱好问卷调查结果进行分析,通过找出强关联规则,准确了解学生的共同爱好,有助于更好地开展校园文化活动.The discovery of association rules is very important for mining the hidden information in the data.This paper studies the association rules mining algorithm,analyzes the process of using FP_Growth algorithm to construct FP-tree and recursive mining frequent itemsets,and analyzes the results of the questionnaire survey of college students interest and hobbies by using the algorithm.By finding out strong association rules,we can accurately understand the common interests of students,and help to better carry out campus cultural activities.

关 键 词：关联规则 频繁项集 FP_GROWTH算法 FP-TREE 条件模式基 

分 类 号：TP311.1[自动化与计算机技术—计算机软件与理论]