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基于相关矩阵的关联规则挖掘及其更新算法 被引量：2

Algorithm for Association Rules Mining Based on Matrix Correlation and Its Updated Algorithm
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摘要 目前已提出的告警序列关联规则挖掘算法都受到最小支持度的限制,仅能够得到频繁告警序列间的关联规则。针对该问题,该文提出一种以高相关度、高置信度为条件,基于相关度统计的挖掘算法。并对其数据更新问题进行了研究,提出一种增量式挖掘算法。实验结果显示,该算法可以高效、准确地挖掘出电信网络告警数据库中频繁和非频繁告警序列间的关联规则。 Currently those algorithms to mine the alarm association rules are just able to obtain the association rules among the frequently occurring alarm events, limiting to the minimal support. To address this problem, a new algorithm based on the statistical correlation is proposed to discover the association rules from both high-frequency and low-frequency alarm events with the high correlativity and the high confidence. And an incremental algorithm is proposed to discover new rules in an updated database. Experimental results have demonstrated that the algorithms are efficient and accurate.
作者 徐前方 肖波 郭军
机构地区 北京邮电大学信息工程学院 北京邮电大学电信工程学院
出处 《计算机工程》 CAS CSCD 北大核心 2008年第1期40-42,46,共4页 Computer Engineering
基金 国家自然科学基金资助项目(60475007) 教育部跨世纪人才基金资助项目
关键词 故障管理 关联规则 数据挖掘 相关度 fault management association rules data mining correlation
分类号 TP391 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献11

  • 1Agrawal R.Mining Association Rules Between Sets of Items in Large Databases[C]//Proceedings of the 1993 ACM SIGMOD Conference.Washington,D.C.:[s.n.],1993.
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二级参考文献14

  • 1Jakobson G,Weissman M D.Alarm correlation[J].IEEE Network.1993,7(6):52-59.
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  • 9Tsai CF, Lin YC, Chen CP. A new fast algorithms for mining association rules in large databases. In: Kamel AE, Mellouli K, Borne P, eds. Proc. Of the 2002 IEEE Int'l Conf. On Systems, Man and Cybernetics (SMC 2002). IEEE Computer Society Press, 2002. 251
  • 10Han J, Pei J, Yin Y. Mining frequent patterns without candidate generation. In: Chen WD, Naughton J, Bernstein PA, eds. Proc. of the 2000 ACM SIGMOD Int'l Conf. on Management of Data (SIGMOD 2000). New York: ACM Press, 2000. 1～12.

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计算机工程
2008年 第1期

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