基于命题逻辑的高度相关关联规则挖掘算法  

Based on Propositional Logic's High Coherent Association Rules Mining Algorithm

作　　者：常浩[1] 贾松浩[2] 杨彩[2] 

机构地区：[1]太原学院,山西太原030012 [2]南阳师范学院,河南南阳473061

出　　处：《忻州师范学院学报》2015年第5期19-24,共6页Journal of Xinzhou Teachers University

基　　金：河南省重点攻关项目(112102210408);河南省基础与前沿技术研究计划项目(112300410225);河南省教育厅科学技术研究重点项目(12A520033);河南省教育厅自然科学研究项目(2011B520029)

摘　　要：数据挖掘是从数据库中发现潜在有用知识或者感兴趣模式的过程。事务数据库中发现关联规则是最常见的数据挖掘,目的在于帮助市场决策者发现事务数据库中项目之间的关联性。文章对关联规则算法进行了研究,通过使用命题逻辑,在最小支持度值未能确定的情况下,直接推导项目之间的关系。该方法把关联规则和等价命题映射起来,形成一种对应关系,如果一个规则满足逻辑相等,那么该规则是一个相关关联规则。通过实例证明了文章提出的高度相关关联规则挖掘算法是有效的,实验也表明该挖掘算法比Apriori算法更有用。Data mining is found from the database potentially useful knowledge or interest in the process model. Transaction association rules found in the database is the most common data mining,is intended to help decision makers find market transaction database correlation between items. Association rules algorithm is studied by using propositional logic,the minimum support value can not be determined in the case,the direct derivation of the relationship between the project,the method of the association rules and equivalence proposition mapped together to form a corresponding relation. If a rule is satisfied logic are equal,then the rule is a relevant association rules. Demonstrated by examples presented in this paper highly relevant association rule mining algorithm is effective. Experiments also show that the mining algorithm is more useful than Apriori algorithm.

关 键 词：数据挖掘 关联规则 命题逻辑 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]