Graph-COM/GAD-NR
[WSDM 2024] GAD-NR : Graph Anomaly Detection via Neighborhood Reconstruction
This project helps detect unusual or suspicious activity within network-like data, such as social connections, transaction histories, or computer network logs. By analyzing the structure and attributes of each connection and node, it identifies individual nodes that behave differently from their neighbors or the overall network pattern. This is ideal for security analysts, fraud investigators, or social media platform managers who need to pinpoint anomalies in complex, interconnected data.
No commits in the last 6 months.
Use this if you need to reliably find various types of unusual nodes—whether they have strange features, form odd connections, or both—within large datasets that can be represented as graphs.
Not ideal if your data is not inherently connected or graph-structured, or if you are looking for anomalies based purely on individual data points without considering their relationships.
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Last pushed
Nov 22, 2024
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