摘要
针对布尔型关联规则不能表达挖掘对象中模糊信息的关联性,给出一系列有关模糊关联规则的定义,并提出一种基于前缀树的模糊关联规则挖掘算法。通过构造前缀树来压缩存储模糊模式候选集和频繁集,有效地节约了内存开销,且只需扫描数据库2遍。实验结果表明,该算法是有效的。
In view of that the boolean association rules can not express the association of fuzzy data, this paper gives a series of definitions of fuzzy association rules and proposes a mining algorithm based on prefix tree for fuzzy association rules. The algorithm can store fuzzy pattern candidate sets and frequent sets compressibly by constructing prefix tree, which effectively saves the memory cost, besides it only scans database twice. The efficiency of the algorithm is verified by the experiment.
出处
《计算机工程》
CAS
CSCD
北大核心
2009年第7期68-69,72,共3页
Computer Engineering
基金
国家自然科学基金资助项目(60603008)
广西教育科学课题基金资助项目(2006A-E004)
关键词
数据挖掘
关联规则
前缀树
模糊模式
data mining
association rule
prefix tree
fuzzy pattern
