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 :
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