An Improved Association Rules Algorithm based on Frequent Item Sets

被引：2

作者：

Jiang, Yaqiong ^{[1
]}

Wang, Jun ^{[2
]}

机构：

[1] Guilin Univ Elect Technol, Network Informat Ctr, Guilin, Peoples R China

[2] Guilin Univ Elect Technol, Dept Finance, Guilin, Peoples R China

来源：

CEIS 2011 | 2011年 / 15卷

关键词：

Association rules; element vector; sub-rule; Improve Algorithm;

D O I：

10.1016/j.proeng.2011.08.625

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, based on the concept of Apriori algorithm for frequent itemsets, adding the element vector, sub-rule and parent-rule, an improved algorithm about association rules mining is proposed. This method overcomes the lack of traditional association rule mining method. It mines the rules while generating the frequent item sets, so the mining efficiency has been improved well. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of [CEIS 2011]

引用

页数：6