DocumentCode
496876
Title
Mining Short Association Rules from Large Database
Author
Ye, Feiyue ; Chen, Mingxia ; Qian, Jin
Author_Institution
Coll. of Comput. Sci. & Eng., Jiangsu Teachers Univ. of Technol., Changzhou, China
Volume
1
fYear
2009
fDate
18-19 July 2009
Firstpage
362
Lastpage
365
Abstract
Discovering association rules from existing large databases is an important technique. In this paper, we propose an effective algorithm for mining short association rules on large database. It is experimentally demonstrated presented algorithm has an advantage over existing algorithm for mining association rule, it has better performance and flexibility. By verifying the real transaction data from a supermarket, the short for mining association rules is effective too.
Keywords
data mining; database management systems; large database; short association rule mining; transaction data verification; Association rules; Computer science; Data engineering; Data mining; Educational institutions; Electronic mail; Information processing; Itemsets; Test pattern generators; Transaction databases; association rule; data mining; frequent pattern;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Processing, 2009. APCIP 2009. Asia-Pacific Conference on
Conference_Location
Shenzhen
Print_ISBN
978-0-7695-3699-6
Type
conf
DOI
10.1109/APCIP.2009.98
Filename
5197071
Link To Document