Intelligent Search of Correlated Alarms from Database containing Noise Data

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Alarm correlation plays an important role in improving the service and reliability in modern telecommunications networks. Most previous research of alarm correlation didn't consider the effect of noise data in Database. This paper focuses on the method of discovering alarm correlation rules from database containing noise data. We firstly define two parameters Winfreq and Winₐdd as the measure of noise data and then present the Robustₛearch algorithm to solve the problem. At different size of Winfreq and Winₐdd, experiments with alarm data containing noise data show that the Robustₛearch Algorithm can discover the more rules with the bigger size of Winₐdd. We also experimentally compare two different interestingness measures of confidence and correlation.