DocumentCode
2739020
Title
An Improved Apriori-based Algorithm for Association Rules Mining
Author
Wu, Huan ; Lu, Zhigang ; Pan, Lin ; Xu, Rongsheng ; Jiang, Wenbao
Author_Institution
Comput. Center, Chinese Acad. of Sci., Beijing, China
Volume
2
fYear
2009
fDate
14-16 Aug. 2009
Firstpage
51
Lastpage
55
Abstract
Because of the rapid growth in worldwide information, efficiency of association rules mining (ARM) has been concerned for several years. In this paper, based on the original Apriori algorithm, an improved algorithm IAA is proposed. IAA adopts a new count-based method to prune candidate itemsets and uses generation record to reduce total data scan amount. Experiments demonstrate that our algorithm outperforms the original Apriori and some other existing ARM methods.
Keywords
data mining; IAA algorithm; apriori-based algorithm; association rules mining; candidate itemsets; count-based method; Association rules; Data mining; Electronic mail; Fuzzy systems; Information management; Information science; Itemsets; Iterative algorithms; Physics computing; Transaction databases; Apriori; association rules mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location
Tianjin
Print_ISBN
978-0-7695-3735-1
Type
conf
DOI
10.1109/FSKD.2009.193
Filename
5358497
Link To Document