• 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