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MINENET
2005
ACM

Topographical proximity for mining network alarm data

10 years 6 months ago
Topographical proximity for mining network alarm data
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. Categories and Subject Descriptors: H.2.8 [Database Management]: Database Applications—Data Mining Gen...
Ann Devitt, Joseph Duffin, Robert Moloney
Added 26 Jun 2010
Updated 26 Jun 2010
Type Conference
Year 2005
Where MINENET
Authors Ann Devitt, Joseph Duffin, Robert Moloney
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