Log Pattern

Log pattern analysis focuses on identifying and interpreting recurring sequences of events within large datasets, primarily system logs, to detect anomalies and improve system understanding. Current research emphasizes efficient log reduction techniques to improve anomaly detection model performance, often employing deep learning architectures like LSTMs and GCNs, alongside clustering methods to pre-process complex log data. This field is crucial for improving the reliability and maintainability of complex systems, enabling proactive identification of failures and facilitating more efficient system monitoring and management.