节点文献
基于向量和矩阵的挖掘关联规则的高效算法
A High Efficiency Algorithm Based on Vectors and Matrix for Mining Associataion Rules
【摘要】 挖掘关联规则是数据挖掘中一个重要的课题,产生频繁项目集是其中的一个关键步骤。文章提出了一种基于向量和矩阵的挖掘算法AVM,并将该算法与两种经典的发现频繁项目集的算法进行了比较。该算法只需要对数据库扫描一遍,并且存放辅助信息所需要的空间也少。实验表明与原先的算法相比,该算法的效率较好。
【Abstract】 Mining association rules is an important problem in data mining.Generating large itemsets is its key.This pa-per presents a novel algorithm based on vectors and matrix for finding frequent itemsets,and compares it with two tra-ditional algorithms.AVM only needs scan the database one time ,and occupies few memory for assistant information.Ex-periment results indicate that the new algorithm has good efficiency compared with presented ones.
【关键词】 数据挖掘;
关联规则频繁项集;
基于向量和矩阵的算法;
【Key words】 Data mining; Association rules; Large itemsets; An algorithm based on vectors and matrix;
【Key words】 Data mining; Association rules; Large itemsets; An algorithm based on vectors and matrix;
- 【文献出处】 计算机工程与应用 ,Computer Engineering and Applications , 编辑部邮箱 ,2004年12期
- 【分类号】TP311
- 【被引频次】42
- 【下载频次】225