DocumentCode
3007414
Title
Research on Improved Data-Mining Algorithm Based on Strong Correlation
Author
Hu, Chunhong ; Wang, Zhengqiang
Author_Institution
Coll. of Comput. Sci., Yangtze Univ., Jingzhou
fYear
2008
fDate
25-26 Sept. 2008
Firstpage
423
Lastpage
426
Abstract
The extensive application of association rules in commerce enables itself to be one of the most active research directions in data mining. Recently, the mining of strong correlation item pairs with statistical significance in transaction database receives a certain value. In order to further reduce the cost of testing candidate item pairs in relational database, we have developed the Taper algorithm according to 1NF property. The developed TaperR algorithm can cut the number of candidate pairs to improve effciency.
Keywords
business data processing; correlation methods; data mining; relational databases; transaction processing; Taper algorithm; association rule; commerce; data-mining algorithm; relational database; strong correlation; transaction database; Algorithm design and analysis; Association rules; Costs; Data mining; Filters; Genetics; Physics computing; Production; Relational databases; Testing; TaperR algorithm; associative rules; correlation coefficient; strong correlation item pairs;
fLanguage
English
Publisher
ieee
Conference_Titel
Genetic and Evolutionary Computing, 2008. WGEC '08. Second International Conference on
Conference_Location
Hubei
Print_ISBN
978-0-7695-3334-6
Type
conf
DOI
10.1109/WGEC.2008.119
Filename
4637477
Link To Document