摘要
典型的关联规则仅考虑事务中所列举的项目,这样的规则主要是正关联规则.负关联规则不但要考虑事务中所包含的项目集,还要考虑事务中所不包含的项目,它有利于进行购物篮分析以发现那些相关的商品或互斥的商品.而已有的负关联规则挖掘的算法具有很大的局限性.为此,文中提出了一种基于位矩阵的负关联规则挖掘新算法.通过算例表明,该算法是有效可行的.
Typical association rules consider only items enumerated in transactions. Such rules are referred to as positive association rules. Negative association rules also consider the same items, but in addition consider negated items （i. e. absent from transactions）. Negative association rules are useful in market-basket analysis to identify products that conflict with each other or products that complement each other. Despite their usefulness, very few algorithms to mine them have been proposed to date. In this paper, a new algorithm based on Bit-matrix for Mining Negative Association Rules （BMNAR） is proposed. The experiments results show that BMNAR is efficient and feasible.
出处
《广西民族大学学报（自然科学版）》
CAS
2007年第4期57-60,共4页
Journal of Guangxi Minzu University ：Natural Science Edition
基金
国家自然科学基金(60461001)
广西自然科学基金(0542048)
梧州学院2007年科研项目(2007C006)
关键词
位矩阵
逻辑运算
负关联规则
数据挖掘
Bit-matrix
Logical computation
Negative association rules
Data mining
