DocumentCode
3335340
Title
An improved Apriori algorithm for association rules of mining
Author
Wei Yong-qing ; Yang Ren-hua ; Liu Pei-yu
Author_Institution
Shandong Police Coll., Ji´nan, China
Volume
1
fYear
2009
fDate
14-16 Aug. 2009
Firstpage
942
Lastpage
946
Abstract
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.
Keywords
data mining; database management systems; association mining rule; business database; data mining process; frequent item set character; improved apriori algorithm; Algorithm design and analysis; Association rules; Data mining; Databases; Educational institutions; Frequency; Information science; Itemsets; Knowledge engineering; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
IT in Medicine & Education, 2009. ITIME '09. IEEE International Symposium on
Conference_Location
Jinan
Print_ISBN
978-1-4244-3928-7
Electronic_ISBN
978-1-4244-3930-0
Type
conf
DOI
10.1109/ITIME.2009.5236211
Filename
5236211
Link To Document