An Improved Apriori Algorithm for Association Rules of Mining

被引:6
|
作者
Wei Yong-qing [1 ]
Yang Ren-hua [2 ]
Liu Pei-yu [2 ]
机构
[1] Shandong Police Coll, Jinan 250014, Peoples R China
[2] Shandong Normal Univ, Sch Informat Sci & Engn, Jinan 250014, Peoples R China
来源
2009 IEEE INTERNATIONAL SYMPOSIUM ON IT IN MEDICINE & EDUCATION, VOLS 1 AND 2, PROCEEDINGS | 2009年
基金
中国国家自然科学基金;
关键词
D O I
10.1109/ITIME.2009.5236211
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Apriori -the classical association rules mining algorithm is a way to find out certain potential, regular knowledge from the massive ones. But there are two more serious defects in the data mining process. The first needs many times to scan the business database and the second will inevitably produce a large number of irrelevant candidate sets which seriously occupy the system resources. An improved method is introduced on the basic of the defects above. The improved algorithm only scans the database once, at the same time the discrete data and statistics related are completed, and the final one is to prune the candidate item sets according to the minimum supporting degree and the character of the frequent item sets. After analysis, the improved algorithm reduces the system resources occupied and improves the efficiency and quality.
引用
收藏
页码:942 / +
页数:2
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