计算机应用研究2012，Vol.29Issue(2)：475-477,3.DOI:10.3969/j.issn.1001-3695.2012.02.019
基于频繁项集挖掘算法的改进与研究
Improved apriori mining frequent items algorithm
刘步中1
作者信息
- 1. 淮安信息职业技术学院电子工程学院,江苏淮安223003
- 折叠
摘要
Abstract
Association rule mining is an important data mining areas of research contents, frequent itemset mining association rules mining is one of the key issues. According to the existing frequent itemset mining algorithm, based on the existing problems , this paper put forward the Apriori algorithm analysis system for Apriori-frequent itemset mining algorithm. The algorithm used overlap strategy to reduce scanning databases, thereby algorithm achieved higher efficiency. Experimental results show that the efficiency of algorithm is 1 ~ 4 times than Apriori system.关键词
数据挖掘/关联规则/频繁项集挖掘算法Key words
data mining/ association rules/ Inter-Apriori分类
信息技术与安全科学引用本文复制引用
刘步中..基于频繁项集挖掘算法的改进与研究[J].计算机应用研究,2012,29(2):475-477,3.
