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快速关联规则挖掘与更新算法 被引量:3

An Fast Algorithm for Data Mining and Incremental Updating on Association Rules
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摘要 一、引言 众所周知,关联规则的挖掘就是发现支持度和信任度分别大于用户指定的最小支持度(mmsup)和最小信任度的规则.支持度不小于minsup的项目集叫频繁项目集;反之,称为非频繁项目集.项目集中项目的数量叫做项目集的维数或长度,项目集X的支持度记作sup(X).有关项目集具有如下性质:(1)如果X是频繁项目集,那么X的任何子集都是频繁项目集;(2)如果X是非频繁项目集,那么X的任何超集都是非频繁项目集. Data Mining and Incremental Updating on Association rules is a major aspect of data mining research. So how to fast discover or update association rules is the research focus. In this papers, we propose a new algorithm for fast data mining and incremental Updating on association rules by the prefix general linked list. Experimented results show that the algorithm not only facilitates the implementation .but also improves the efficiency .and avoids producing combinatorial explosion problem.
作者 杨明 孙志挥
出处 《计算机科学》 CSCD 北大核心 2002年第8期88-90,共3页 Computer Science
基金 国家自然科学基金(项目编号79970092) 安徽省教育厅自然科学研究基金(项目编号2001kj050)
关键词 数据库 数据挖掘 关联规则挖掘算法 PGLIUA算法 Prefix general linked list. Association rules Incremental updating. Data mining
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参考文献12

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二级参考文献3

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