Boosting Log Anomaly Detection with NLP and Deep Learning
This article presents a log anomaly detection approach that leverages NLP techniques such as Part‑of‑Speech tagging and Named Entity Recognition combined with deep neural networks, detailing a six‑step model, experimental validation on three datasets, and superior performance compared with existing DeepLog and LogClass methods.