On the Effectiveness of Log Representation for Log-based Anomaly Detection

arXiv:2308.08736v3 Announce Type: replace-cross
Abstract: Logs are an essential source of information for people to understand the running status of a software system. Due to the evolving modern software architecture and maintenance methods, more research efforts have been devoted to automated log analysis. In particular, machine learning (ML) has been widely used in log analysis tasks. In ML-based log analysis tasks, converting textual log data into numerical feature vectors is a critical and indispensable step. However, the impact of using …

abstract analysis anomaly anomaly detection architecture arxiv automated cs.lg cs.se detection information logs machine machine learning maintenance modern people representation research running software software architecture type