事务间数值型关联规则的挖掘  

Mining Inter-transactional Quantitative Association Rules

作　　者：邓景毅[1] 张小康[2] 

机构地区：[1]广东商学院信息学院,广东广州510320 [2]暨南大学信息学院计算机科学系,广东广州510632

出　　处：《计算机应用》2004年第4期38-41,共4页journal of Computer Applications

基　　金：广东省自然科学基金资助项目(020199)

摘　　要：关联规则的发现是整个数据挖掘课题中的重要组成部分。在归纳现有关联规则研究的基础上提出了事务间数值型关联规则的数据挖掘问题,并对该问题进行了定义。应用模糊理论和相关的数据挖掘技术,提出了解决该问题的E QA算法,并以实例对算法可行性进行验证,指出了算法存在的一些问题以及今后解决这些问题的思路。Mining association rules is an important part of data mining. Based on the summarization of data mining research,the problem of mining inter-transactional quantitative association rules are brought forward and defined in this paper. Applying the fuzzy set concepts and related data mining algorithms,E-QA algorithm is brought forward. Experiments are made to verify the performance of the algorithm. At the end of this paper,some problems of the algorithm are proposed and some possible ways to solve them are brought forward.

关 键 词：事务间关联规则 数据挖掘 模糊集 数值型数据 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]