Enhancing Fairness in Unsupervised Graph Anomaly Detection through Disentanglement

Graph anomaly detection (GAD) is increasingly crucial in various applications, ranging from financial fraud detection to fake news detection. However, current GAD methods largely overlook the fairness problem, which might result in discriminatory decisions skewed toward certain demographic groups de...

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Hauptverfasser:	Chang, Wenjing, Liu, Kay, Yu, Philip S, Yu, Jianjun
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Computers and Society Computer Science - Learning Computer Science - Social and Information Networks
Online-Zugang:	Volltext bestellen
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