Outlier and anomalous behavior detection in social networks using constraint programming

Abstract

Outlier and anomaly detection are widely used in several fields of study such as social networks, statistics, and knowledge discovery. In social networks, it is useful to detect structural abnormalities which are different from the typical behavior of the social network in order to maintain the network security and privacy. In this paper, we suggest a new… (More)
DOI: 10.1109/AICCSA.2016.7945699

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