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Graph based anomaly detection and description: a survey
2014
Data mining and knowledge discovery
Detecting anomalies in data is a vital task, with numerous high-impact applications in areas such as security, finance, health care, and law enforcement. While numerous techniques have been developed in past years for spotting outliers and anomalies in unstructured collections of multi-dimensional points, with graph data becoming ubiquitous, techniques for structured graph data have been of focus recently. As objects in graphs have long-range correlations, a suite of novel technology has been
doi:10.1007/s10618-014-0365-y
fatcat:rfjn7bwdgra5faorwbdkkb45ze