Improvement of Apriori Algorithm Based on Vector and Vertical Array

被引：0

作者：

Guo, Zhen-yu ^{[1
]}

Chen, Tian-huang ^{[1
]}

机构：

[1] Wuhan Univ Technol, Wuhan 430063, Peoples R China

来源：

INTERNATIONAL CONFERENCE ON CONTROL AND AUTOMATION (ICCA 2016) | 2016年

关键词：

Data mining; Association analysis; Apriori algorithm; Vector array; Vertical array;

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：

In the data mining method of association analysis, the classic Apriori algorithm of discovering frequent item sets may multiple scanning the source database, produce a large number of candidate and repeatedly pattern matching, which leads to low time efficiency of the algorithm. Based on the analysis of the array based algorithm, an improved algorithm is proposed in this paper. The main idea is to scan the source database once and use vector arrays and vertical arrays to represent the transactions, improve the strategy of the join step and the prune step when candidate frequent(k+1)-item sets were generated from frequent(K)-item sets as well as the pattern matching strategy. The experimental results show that the time complexity of the improved algorithm is reduced greatly.

引用

页码：619 / 625

页数：7