AN INCREMENTAL UPDATING ALGORITHM FOR MINING ASSOCIATION RULES

作     者：Xu Baowen Yi Tong Wu Fangjun Chen Zhenqiang(Department of Computer Science & Engineering, Southeast University, Nanjing 210096) (National Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072) Xu Baowen Yi Tong Wu Fangjun Chen Zhenqiang(Department of Computer Science & Engineering, Southeast University, Nanjing 210096) (National Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072)

作者机构：Department of Computer Science & Engineering Southeast University Nanjing 210096 National Key Laboratory of Software Engineering Wuhan University Wuhan 430072 Department of Computer Science & Engineering Southeast University Nanjing 210096 

出 版 物：《Journal of Electronics(China)》 (电子科学学刊（英文版）)

年 卷 期：2002年第19卷第4期

页      面：403-407页

学科分类：0810[工学-信息与通信工程] 08[工学] 080401[工学-精密仪器及机械] 0804[工学-仪器科学与技术] 080402[工学-测试计量技术及仪器] 0835[工学-软件工程] 081002[工学-信号与信息处理] 

基　　金：Supported in part by the National Natural Science Foundation of China(No.60073012) Natural Science Foundation of Jiangsu(BK2001004) 

主　　题：Data mining Association rules Support function Frequent pattern tree 

摘      要：In this letter, on the basis of Frequent Pattern(FP) tree, the support function to update FP-tree is introduced, then an Incremental FP (IFP) algorithm for mining association rules is proposed. IFP algorithm considers not only adding new data into the database but also reducing old data from the database. Furthermore, it can predigest five cases to three *** algorithm proposed in this letter can avoid generating lots of candidate items, and it is high efficient.