摘要
针对已有周期性关联规则模型的局限性 ,本文提出一种新的周期性关联规则模型。此模型通过聚类分析将一个周期分成若干个长度可能不同的时间段 ,从而更准确地发现周期性关联规则。文章还给出相应的挖掘算法。
To overcome the limitation of existing models,the paper proposes a new model of cyclic association rules which can discover cyclic association rules more precisely by dividing a cycle into several time segments of possibly different lengths through clustering analysis.The corresponding algorithm is also given.
出处
《计算机工程与科学》
CSCD
2000年第4期78-81,共4页
Computer Engineering & Science
基金
江苏省自然科学基金!资助项目 ( BK970 0 2 )
关键词
数据挖掘
周期性关联规则
聚类分析
数据库
data mining
association rules
cyclic association rules
clustering analysis
