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Article Navigation >  Journal of University of Electronic Science and Technology of China  > 2008  >  37(6): 807-810

LI Tong-yan, XIAO Hai-lin, LI Xing-ming. Algorithm for Mining Weighted Alarm Association Rules in Telecommunication Networks[J]. Journal of University of Electronic Science and Technology of China, 2008, 37(6): 807-810.
Citation: LI Tong-yan, XIAO Hai-lin, LI Xing-ming. Algorithm for Mining Weighted Alarm Association Rules in Telecommunication Networks[J]. Journal of University of Electronic Science and Technology of China, 2008, 37(6): 807-810.
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Algorithm for Mining Weighted Alarm Association Rules in Telecommunication Networks

  • 1.

    Key Laboratory of Ministry of Education for Broadband Optical Fiber Transmission and Communication Networks,University of Electronics Science and Technology of China Chengdu 610054

  • Received Date: 2007-06-18
  • Rev Recd Date: 2007-12-21
  • Publish Date: 2008-12-15
  • Mining association rules is one of the primary methods used in telecommunication alarm correlation analysis. The efficiency of the algorithms plays an important role in tackling with large datasets. A highly efficient algorithm of weighted association rules mining in telecommunication networks based on weighted frequent pattern tree is proposed. The performance test of the algorithm indicates that compared with other algorithms of weighted association rules mining, this one needs less memory and has higher temporal efficiency, which is significant for the network fault diagnosis and localization.
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  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

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Algorithm for Mining Weighted Alarm Association Rules in Telecommunication Networks

  • 1. Key Laboratory of Ministry of Education for Broadband Optical Fiber Transmission and Communication Networks,University of Electronics Science and Technology of China Chengdu 610054
  • Received Date: 2007-06-18
  • Rev Recd Date: 2007-12-21
  • Publish Date: 2008-12-15

Abstract: Mining association rules is one of the primary methods used in telecommunication alarm correlation analysis. The efficiency of the algorithms plays an important role in tackling with large datasets. A highly efficient algorithm of weighted association rules mining in telecommunication networks based on weighted frequent pattern tree is proposed. The performance test of the algorithm indicates that compared with other algorithms of weighted association rules mining, this one needs less memory and has higher temporal efficiency, which is significant for the network fault diagnosis and localization.

LI Tong-yan, XIAO Hai-lin, LI Xing-ming. Algorithm for Mining Weighted Alarm Association Rules in Telecommunication Networks[J]. Journal of University of Electronic Science and Technology of China, 2008, 37(6): 807-810.
Citation: LI Tong-yan, XIAO Hai-lin, LI Xing-ming. Algorithm for Mining Weighted Alarm Association Rules in Telecommunication Networks[J]. Journal of University of Electronic Science and Technology of China, 2008, 37(6): 807-810.
shu

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