Title :
A data clustering algorithm for mining patterns from event logs
Author_Institution :
Dept. of Comput. Eng., Tallinn Tech. Univ., Estonia
Abstract :
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.
Keywords :
data mining; pattern clustering; software tools; telecommunication computing; telecommunication network management; data clustering algorithm; data mining; event logs; log file data sets; network management; pattern mining; simple log file clustering tool; syslog protocol; system management; Association rules; Clustering algorithms; Data engineering; Data mining; Databases; Event detection; Fault detection; Monitoring; Pattern matching; Protocols;
Conference_Titel :
IP Operations & Management, 2003. (IPOM 2003). 3rd IEEE Workshop on
Print_ISBN :
0-7803-8199-8
DOI :
10.1109/IPOM.2003.1251233
