Association Rules Mining Algorithm based on Matrix

被引：0

作者：

Ma, Lei ^{[1
]}

机构：

[1] Linyi Univ, Dept Media, Linyi 276000, Peoples R China

来源：

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ADVANCES IN MECHANICAL ENGINEERING AND INDUSTRIAL INFORMATICS | 2015年 / 15卷

关键词：

Data Mining; Association Rules; Frequent Itemsets; Matrix;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Association rules mining is an important model in data mining. The classic Apriori algorithm for Association rules need scan database many times and generate a great deal of candidate itemsets. This paper proposes a new algorithm for mining association rules based on matrix. The algorithm scans database only once to generate matrix of transaction and item, which generates candidate itemsets by using matrix. The experimental results of the algorithm show that the new algorithm is more efficient than traditional algorithm.

引用

页码：974 / 980

页数：7

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