Exploiting network topology in mining sequential patterns from telecommunications alarm data
Citation:
Ann Devitt, Joseph Duffin and Robert Moloney, Exploiting network topology in mining sequential patterns from telecommunications alarm data, MineNet Workshop at SIGCOMM 2005, Philadelphia, USA, August 2005, 2005, 179 - 184Download Item:
Sigcomm2005devitt-duffin-moloney.pdf (published (publisher copy) peer-reviewed) 136.1Kb
Abstract:
Increasingly powerful fault management systems are required
to ensure robustness and quality of service in today?s networks.
In this context, event correlation is of prime importance
to extract meaningful information from the wealth of
alarm data generated by the network. Existing sequential
data mining techniques address the task of identifying possible
correlations in sequences of alarms. The output sequence
sets, however, may contain sequences which are not plausible
from the point of view of network topology constraints.
This paper presents the Topographical Proximity (TP) approach
which exploits topographical information embedded
in alarm data in order to address this lack of plausibility
in mined sequences. An evaluation of the quality of mined
sequences is presented and discussed. Results show an improvement
in overall system performance for imposing proximity
constraints.
Author's Homepage:
http://people.tcd.ie/devittanDescription:
PUBLISHEDPhiladelphia, USA
Author: Devitt, Ann
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MineNet Workshop at SIGCOMM 2005Type of material:
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Full text availableKeywords:
data mining, telecommunications network alarmsSubject (TCD):
Intelligent Content & CommunicationsLicences: