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Fraud is a social process that occurs over time. We introduce a new approach, called AFRAID, which utilizes active inference to better detect fraud in time-varying social networks. That is, classify nodes as fraudulent vs. non-fraudulent. In active inference on social networks, a set of unlabeled nodes is given to an oracle (in our case one or more fraud inspectors) to label. These labels are used...
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