Alarm association rule mining method, and rule mining engine and system

Abstract

The embodiment of the invention discloses an alarm association rule mining method, an alarm association rule mining engine and an alarm association rule mining system. The method comprises the following steps of: acquiring an alarm sequence, wherein the alarm sequence comprises multiple pieces of alarm; calculating support of each k-item set to obtain a k-item frequency item set aggregate; generating a k+1-item frequency item set aggregate from the k-item frequency item set aggregate; calculating maximum degree of confidence of the k+1-item frequency item set aggregate according to the maximum value in the support of k+1 1-item sets included in the k+1-item frequency item set and the support of the k+1-item frequency item set for each k+1-item frequency item set in the k+1-item frequency item set aggregate; adding the k+1-item frequency item set with the maximum degree of confidence no less than minimum degree of confidence into an association rule result set as an association rule; and thus a false rule produced due to the influence of the parameter of the degree of confidence is reduced and the false rule in the association rule result set is effectively reduced during the mining of the alarm association rule.

Description

technical field [0001] The embodiments of the present invention relate to the field of communication technologies, and in particular, relate to a method for mining an alarm association rule, a rule mining engine and a system. Background technique [0002] During the operation of the communication network, a large number of alarms are generated by telecommunication equipment every day, and the failure of one equipment will cause other equipment to generate alarms. In the 1970s, someone proposed to use a rule engine to automatically process telecom alarms according to alarm association rules. With the development of the network, the network structure becomes more and more complex, and the relationship between telecommunication devices becomes more and more complicated, which makes it difficult to define the alarm correlation rules manually. [0003] In the field of alarm association rule mining, it was proposed to apply frequent pattern mining technology to the mining of alar...

AI Technical Summary

Problems solved by technology

There is actually no correlation between alarm A and alarm B (because no matter whether alarm B occurs or not, the probability of alarm A occurring is close to 100%), but in the application process of mining alarm association rules using the existing WinEPI algorithm, it will be mistaken for There is a strong correlation between alarm A and alarm B (that is, the pattern is a strong association rule), so there will be false rules in the association rule result set output by the prior art

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