基于排序向量内积的关联规则挖掘算法  

Association rule algorithm based on order vectors inner product

作　　者：梁宝华[1] 张步群[1] 陆军[1] 蔡敏[1] 

机构地区：[1]巢湖学院计算机科学与技术系,安徽巢湖238000

出　　处：《计算机工程与应用》2008年第26期126-128,165,共4页Computer Engineering and Applications

基　　金：安徽省级自然科学研究项目(No.KJ2008A35ZC)

摘　　要：关联规则发现是数据挖掘中的重要研究课题之一。将挖掘的数据事务集压缩到一个布尔型向量矩阵中,只需扫描数据库一次,合理利用数据存储结构,且不会产生大量的候选集。实验表明,该算法不仅实现简单,与经典的Apriori算法进行相比,效率也有大幅提高,特别对大事务集、长项目集数据挖掘效果更为明显。Association rules discovery is an important research topic in data mining.The article will mine Data-Item set compression to a Boolean Vector Matrix.The algorithm only needs to scan the database one time and rational use of data storage structure so that it would not generate a large number of candidate sets.Experiment results indicate that the algorithm is not only simple,but also has good efficiency compared with the Apriori algorithm.When you mine a large database and long item-set,the mining effect of this way is more visible than the Apriori algorithm.

关 键 词：数据挖掘 关联规则 频繁项集 向量内积 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]