Efficient Event Log Mining with LogClusterC
Chen Zhuge, Risto Vaarandi · 2017
Nowadays, many organizations collect large volumes of event log data on a daily basis, and the analysis of collected data is a challenging task. For this purpose, data mining methods have been suggested in past research papers, and several data clustering algorithms have been developed formining line patterns from event logs. In this paper, we introduce an open-source tool called LogClusterC which implements the LogCluster algorithm for discovering line patterns and outliers from event logs. According to our performance measurements, LogClusterC compares favorablyto other publicly available log clustering tools.