| 基于相关矩阵的关联规则挖掘及其更新算法 |
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| 引用本文： | 徐前方,肖波,郭军.基于相关矩阵的关联规则挖掘及其更新算法[J].计算机工程,2008,34(1):40-42,4. |
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| 作者姓名： | 徐前方 肖波 郭军 |
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| 作者单位： | 1. 北京邮电大学信息工程学院,北京,100876
2. 北京邮电大学电信工程学院,北京,100876 |
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| 基金项目： | 国家自然科学基金
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教育部跨世纪优秀人才培养计划 |
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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。
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| 关 键 词： | 故障管理 关联规则 数据挖掘 相关度 |
| 文章编号： | 1000-3428（2008）01-0040-03 |
| 收稿时间： | 2007-02-22 |
| 修稿时间： | 2007年2月22日 |
Algorithm for Association Rules Mining Based on Matrix Correlation and Its Updated Algorithm |
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| XU Qian-fang,XIAO Bo,GUO Jun.Algorithm for Association Rules Mining Based on Matrix Correlation and Its Updated Algorithm[J].Computer Engineering,2008,34(1):40-42,4. |
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| Authors: | XU Qian-fang XIAO Bo GUO Jun |
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| Affiliation: | (1. College of Information Engineering, Beijing University of Posts & Telecommunications, Beijing 100876; 2. Telecommunication Engineering School, Beijing University of Posts & Telecommunications, Beijing 100876) |
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| Abstract: | 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. |
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| Keywords: | fault management association rules data mining correlation |
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