DocumentCode :
2645960
Title :
New Criterion for Mining Strong Association Rules in Unbalanced Events
Author :
Tong-Yan Li ; Xing-Ming Li
Author_Institution :
Key Lab. of Broad-band Opt. Fiber Transm. & Commun. Syst., UESTC, Chengdu
fYear :
2008
fDate :
15-17 Aug. 2008
Firstpage :
362
Lastpage :
365
Abstract :
Association rules mining is an important task in data mining and the normal measures support and confidence are useful for finding association rules between the items. However, the process of finding frequent items would prune infrequent items which may include some useful relationships of association patterns. The new measures comsup, comcof and comsup´ are proposed to resolve this problem effectively. By comparison and taking examples, these new measures proved to be effective in the special situation, and some interesting rules could be found in the unbalanced events in which include the infrequent items.
Keywords :
data mining; pattern clustering; association patterns; association rules mining; data mining; infrequent items; unbalanced events; Association rules; Data mining; Equipment failure; Multimedia systems; Optical fiber communication; Optical fiber devices; Optical signal processing; Probability; Statistical analysis; Transaction databases; Association rules mining; confidence; infrequent items; support;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Information Hiding and Multimedia Signal Processing, 2008. IIHMSP '08 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-0-7695-3278-3
Type :
conf
DOI :
10.1109/IIH-MSP.2008.73
Filename :
4604076
Link To Document :
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