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A rule induction approach to forecasting critical alarms in a telecommunication network

Wrench, C., Stahl, F., Di Fatta, G., Karthikeyan, V. and Nauck, D. (2019) A rule induction approach to forecasting critical alarms in a telecommunication network. In: 2019 IEEE International Conference on Data Mining Workshops (ICDMW), 8-11 Nov 2019, Beijing, China. (In Press)

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Abstract/Summary

This paper proposes a white box method of predicting critical alarms so they can be mitigated and understood by engineers. Forecasting these alarms will avoid outages and maintain the agreed service level which is beneficial to both the provider of telecommunication services and the consumers. The paper evaluates several item set mining approaches on a set of alarms of the British Telecom (BT) national telecommunication network and proposes a novel transformation of the data to enable the discovery of patterns undetectable by current item set mining approaches. The result is a method for rule induction that predicts alarms with high precision using a wide range of features.

Item Type:Conference or Workshop Item (Paper)
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:87006

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