Mining Alarm Association Rules Based on Comprehensive Related Confidence

Huisheng Gao; Yingmin Li

doi:10.3969/j.issn.1000-0801.2014.10.017

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Mining Alarm Association Rules Based on Comprehensive Related Confidence

Research And Development | 更新时间：2024-06-05

- Mining Alarm Association Rules Based on Comprehensive Related Confidence
- Telecommunications Science Vol. 30, Issue 10, Pages: 110-115(2014)
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- DOI：10.3969/j.issn.1000-0801.2014.10.017
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- Published Online：2014-10，
  
  Published：20 October 2014
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Huisheng Gao, Yingmin Li. Mining Alarm Association Rules Based on Comprehensive Related Confidence[J]. Telecommunications science, 2014, 30(10): 110-115.
DOI：

Huisheng Gao, Yingmin Li. Mining Alarm Association Rules Based on Comprehensive Related Confidence[J]. Telecommunications science, 2014, 30(10): 110-115. DOI： 10.3969/j.issn.1000-0801.2014.10.017.

摘要

采用置信度融合算法计算相邻告警的综合相关置信度，并根据计算结果形成告警关联事务，增强告警事务内告警之间的相关性，降低对支持度的选择要求，有效挖掘出“低支持度-置信度”告警关联规则。利用h-置信度理论筛选有意义的告警关联规则，并通过实验比较了传统方法和本文方法的执行效率和挖掘正确率。

Abstract

The traditional association rules mining algorithms preferred to applying single sliding time window

and the mined alarm association rules were high support-high confidence. To solve this problem

a method was proposed to calculate comprehensive related confidence between the time adjacent items by the confidence fusion algorithm. Then generated alarm transactions were generated based on the calculated results

which enhanced alarm correlation within a transaction. The proposed approach can reduce the choice of support requirement and mine low support-high confidence association rules effectively. Based on h-confidence theory

interesting alarm association rules were screened. Experimental results showed the feasibility and effectiveness of this approach.

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references

Mannila H , Toivonen H Verkamo I A ． Discovery of frequent episodes in event sequences . Data Mining and Knowledge Discovery , 1997 ( 1 )

徐前方，肖波，郭军．挖掘电信告警关联模式方法．北京邮电大学学报， 2011 ， 34 ( 2 ): 86 ～ 89

夏英，张俊，王国胤．时空关联规则挖掘算法及其在ITS中的应用．计算机科学， 2011 ， 38 ( 9 ): 173 ～ 176

Lagzian S , Amiri F , Enayati A . Frequent item set mining-based alert correlation for extracting multi-stage attack scenarios . Proceedings of the 6th International Symposium on Digital Object Identifier , Iran, Tehran , 2012

田志宏，张永铮，张伟哲等 . 基于模式挖掘和聚类分析的自适应告警关联．计算机研究与发展， 2009 , 46 ( 8 ): 1304 ～ 1315

吴简，李兴明．基于关联规则的分布式通信网告警相关性研究．计算机科学， 2009 ， 36 ( 11 ): 204 ～ 207

Han J W . Mining frequent patterns without candidate generation . Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data , New York, USA , 2000

刘镜，刘加．置信度的原理及其在语音识别中的应用．计算机研究与发展， 2000 ， 37 ( 7 ): 882 ～ 889

王海栋，郑骁庆，张红俊．基于置信度理论的网络知识融合系统和应用．计算机系统应用， 2011 ， 20 ( 1 ): 1 ～ 6

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