通信网告警加权关联规则挖掘算法的研究  

Algorithm for Mining Weighted Alarm Association Rules in Telecommunication Networks

作　　者：李彤岩[1] 肖海林[1] 李兴明[1] 

机构地区：[1]电子科技大学宽带光纤传输与通信网技术教育部重点实验室,成都610054

出　　处：《电子科技大学学报》2008年第6期807-810,共4页Journal of University of Electronic Science and Technology of China

基　　金：国家自然科学基金(60572091)

摘　　要：关联规则挖掘算法是通信网告警相关性分析中的重要方法。在处理数量庞大的告警数据库时,算法的效率显得至关重要,而经典的FP-growth算法会产生大量的条件模式树,加权算法MINWAL(O)则需要多次扫描数据库,使得在通信网环境下挖掘关联规则的难度非常大。该文提出了一种高效的基于加权频繁模式树的通信网告警关联规则挖掘算法,算法性能测试表明,该算法与已有的加权关联规则挖掘算法相比较,节约了大量的存储空间,提高了算法的挖掘速度,对通信网的故障诊断和故障定位有着积极的意义。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.

关 键 词：告警相关性分析 故障诊断 故障定位 加权关联规则 加权频繁模式树 

分 类 号：TN915.07[电子电信—通信与信息系统]