摘要: 提出了一种新颖的普遍化关联规则挖掘算法GARL。该算法连续扫描数据库事务序列,在最多不超过两遍扫描后生成所有频繁项目集,在首次扫描数据库时,能为用户给出反馈信息,允许用户对最小支持率进行调整,该算法能连续处理事务序列,可用于网上在线数据挖掘。
关键词:
知识发现,
数据挖掘,
关联规则,
普遍化关联规则
Abstract: A novel algorithm GARL for mining generalized association rules is proposed. It continuously scans transaction sequences in database and produces a set of all frequent itemsets for a user-specified m inimum support after at most two scans. During the first scan of the database, it can give continuous feedback and allows user to change the minimum support. GARL processes a transaction sequences continuously and can be used for on-line data mining on network.
中图分类号:
李乃乾,沈钧毅,田絮资. 一种新的普遍化关联规则挖掘算法[J]. , 2003, 29(07): 9-11.
LI Naiqian,SHEN Junyi. A Novel Algorithm for Mining Generalized Association Rules[J]. , 2003, 29(07): 9-11.