Semi-supervised Anomaly Detection on Attributed Graphs

27 Feb 2020Atsutoshi KumagaiTomoharu IwataYasuhiro Fujiwara

We propose a simple yet effective method for detecting anomalous instances on an attribute graph with label information of a small number of instances. Although with standard anomaly detection methods it is usually assumed that instances are independent and identically distributed, in many real-world applications, instances are often explicitly connected with each other, resulting in so-called attributed graphs... (read more)

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