  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 Win_freq and
Win_add as the measure of noise data and then present the Robust_search
algorithm to solve the problem. At different size of Win_freq and Win_add,
experiments with alarm data containing noise data show that the Robust_search
Algorithm can discover the more rules with the bigger size of Win_add. We also
experimentally compare two different interestingness measures of confidence and
correlation.
