A data clustering algorithm for mining patterns from event logs

Today, event logs contain vast amounts of data that can easily overwhelm a human. Therefore, mining patterns from event logs is an important system management task. The paper presents a novel clustering algorithm for log file data sets which helps one to detect frequent patterns from log files, to b...

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Bibliographic Details
Published inProceedings of the 3rd IEEE Workshop on IP Operations & Management : (IPOM2003) Kansas City, Missouri, USA, October 1-3, 2003 pp. 119 - 126
Main Author Vaarandi, R.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2003
Subjects
Association rules
Clustering algorithms
Data engineering
Data mining
Event detection
Fault detection
Monitoring
Pattern matching
Protocols
Online AccessGet full text
ISBN9780780381995
0780381998
DOI10.1109/IPOM.2003.1251233

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Summary:Today, event logs contain vast amounts of data that can easily overwhelm a human. Therefore, mining patterns from event logs is an important system management task. The paper presents a novel clustering algorithm for log file data sets which helps one to detect frequent patterns from log files, to build log file profiles, and to identify anomalous log file lines.
ISBN:9780780381995
0780381998
DOI:10.1109/IPOM.2003.1251233