Towards Expressive Rule Induction on IP Network Event Streams

Wrench, Chris; Stahl, Frederic; Fatta, Giuseppe Di; Karthikeyan, Vidhyalakshmi; Nauck, Detlef

doi:10.1007/978-3-319-25032-8_14

Cited by 2 publications

(1 citation statement)

References 10 publications

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“…As ITRULE and the J-Measure make frequent appearances in Section II a variety of algorithms from that family are trialled. These are ITRULE; ITRULE PRD [31], a variant of ITRULE actively combats Partial Rule Dominance (PRD), a form of over-fitting; a variant using simulated annealing to handle over fitting; and a variant based on eXpose [17] from the literature, referred to as ITRULE Positive. Figure 7 shows the precisions of all the rule induction algorithms across the time windows as the output of the Two Stage system.…”

Section: B Rule Induction Of Pre-eventsmentioning

confidence: 99%

A Rule Induction Approach to Forecasting Critical Alarms in a Telecommunication Network

Wrench

Stahl

Fatta

et al. 2019

2019 International Conference on Data Mining Workshops (ICDMW)

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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.

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Section: B Rule Induction Of Pre-eventsmentioning

confidence: 99%

A Rule Induction Approach to Forecasting Critical Alarms in a Telecommunication Network

Wrench

Stahl

Fatta

et al. 2019

2019 International Conference on Data Mining Workshops (ICDMW)

Self Cite

View full text Add to dashboard Cite

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A Method of Rule Induction for Predicting and Describing Future Alarms in a Telecommunication Network

Wrench

Stahl

et al. 2016

Research and Development in Intelligent Systems XXXIII

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In order to gain insights into events and issues that may cause alarms in parts of IP networks, intelligent methods that capture and express causal relationships are needed. Methods that are predictive and descriptive are rare and those that do predict are often limited to using a single feature from a vast data set. This paper follows the progression of a Rule Induction Algorithm that produces rules with strong causal links that are both descriptive and predict events ahead of time. The algorithm is based on an information theoretic approach to extract rules comprising of a conjunction of network events that are significant prior to network alarms. An empirical evaluation of the algorithm is provided.

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Towards Expressive Rule Induction on IP Network Event Streams

Cited by 2 publications

References 10 publications

A Rule Induction Approach to Forecasting Critical Alarms in a Telecommunication Network

A Rule Induction Approach to Forecasting Critical Alarms in a Telecommunication Network

A Method of Rule Induction for Predicting and Describing Future Alarms in a Telecommunication Network

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