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Industrial log analysis revisited: A task-oriented evaluation of parsing and anomaly detection under real-world constraints
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DOI：10.1016/j.infsof.2026.108205.png)
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Abstract
En 中文
Log analysis is a critical component for monitoring, diagnosis, and risk mitigation in software systems. However, most existing research evaluates log parsing and anomaly detection models on benchmark datasets derived from legacy or open-source systems, which fail to reflect the structural diversity, semantic density, and annotation constraints of real-world industrial logs. In industrial settings, detected anomalies can support early warning, root-cause localization, preventive maintenance, and operational risk control.
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