DocumentCode
468988
Title
Study of the neural network applied to weighted association rules mining
Author
Li, Tong-yan ; Li, Xing-ming
Author_Institution
Key Lab. of Broadband Opt. Fiber Transmission & Commun. Network of Minist. of Educ., Chengdu
Volume
2
fYear
2007
fDate
2-4 Nov. 2007
Firstpage
742
Lastpage
745
Abstract
The mining of weighted association rules is one of the primary methods used in telecommunication alarm correlation analysis, of which weight set is a difficulty. In this study, we propose a novel method which uses neural network to identify the alarm weight. The neural network has three inputs with the key elements which reflect the importance of the telecommunication alarm. After the course of sample training, we will get the link weight. The weight of the neural network may reflect the knowledge of the experts and also can be changed automatically with the different items from the inputs. Modeling and simulation study indicate that compared with other methods of measuring alarm weight, the neural network method has more advantages.
Keywords
data mining; neural nets; telecommunication computing; telecommunication services; experts knowledge; neural network; telecommunication alarm correlation analysis; weighted association rules mining; Algorithm design and analysis; Association rules; Data mining; Laboratories; Neural networks; Notice of Violation; Optical fibers; Pattern analysis; Pattern recognition; Wavelet analysis; alarm correlation analysis; link weight; neural network; weighted association rules;
fLanguage
English
Publisher
ieee
Conference_Titel
Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-1065-1
Electronic_ISBN
978-1-4244-1066-8
Type
conf
DOI
10.1109/ICWAPR.2007.4420767
Filename
4420767
Link To Document