An Improved Apriori Algorithm

被引：0
|
作者：
Gu, Jianlong [1 ]
Wang, Baojin [2 ]
Zhang, Fengyu [2 ]
Wang, Weiming [1 ]
Gao, Ming [1 ]
机构：
[1] Xiasha Univ, Zhejiang Gongshang Univ, Coll Informat & Elect Engn, 18 Xuezheng Str, Hangzhou 310018, Peoples R China
[2] PLA Informat Engn Univ, Natl Digital Switch Syst Engn & Technol R&D Ctr, Zhengzhou 450002, Peoples R China
来源：
2010 THE 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND INDUSTRIAL APPLICATION (PACIIA2010), VOL I | 2010年
基金：
中国国家自然科学基金;
关键词：
Data mining; Association rules; Apriori algorithm;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Association rules mining occupies an important position in data mining. In order to improve the efficiency of mining of frequent itemsets, contrapose the two key problems of reducing the times of scaning the transactional database and reducing the number of candidate item sets, an improved algorithm is presented based on the classic Apriori algorithm. The theoretical analysis and test results show that the improved algorithm is better than Apriori algorithm significantly on efficiency.
引用
收藏
页码：84 / 86
页数：3
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