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Research questionHow can dynamic-graph anomaly detection capture short-term interaction behavior in event streams?Raw event-stream representations can overlook behaviors such as sender intensity and interaction inertia. This makes anomalies driven by brief changes in interaction patterns difficult to distinguish from normal activity.
AI
Machine Learning
Research Paper
Statistical Machine Learning
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Latest papersRecent research connected to this question, newest first.Statistical Feature Augmentation for Anomaly Detection in Dynamic GraphsThe study evaluates statistical feature augmentation for anomaly detection using Reddit, Wikipedia, and MOOC event data. It applies the same augmented features across seven continuous-time and discrete-time deep graph models and compares them with models trained on the original embeddings; the dedicated statistical dimensions also support post-hoc analysis of behavioral importance.research paper · Sep 2, 2026
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