geon0325/HashNWalk
Source code for IJCAI 2022 paper "HashNWalk: Hash and Random Walk Based Anomaly Detection in Hyperedge Streams."
This tool helps detect unusual activity in complex group interactions, like email threads or online discussions, as they happen. You feed it a continuous stream of events, where each event represents a group of participants and a timestamp. It then identifies and flags any new group interaction that seems out of the ordinary, providing a score for how anomalous it is. This is ideal for analysts monitoring dynamic systems where multiple entities interact.
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Use this if you need to quickly spot abnormal patterns in how groups of people or entities interact over time, without having to manually review vast amounts of data.
Not ideal if your data represents simple one-to-one connections or if you need to detect anomalies in static, unchanging datasets rather than real-time streams.
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Last pushed
May 09, 2022
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