FRAUD DETECTION IN DATA SETS USING BAYESIAN NETWORKS

摘要

A computer-implemented method can include receiving multiple survey response sets, where each survey response set includes the responses of a survey taker. A maximum weight spanning tree can be defined. Each node of the maximum weight spanning tree can represent a survey question. Directional edges can connect nodes. A weight for each directional edge can be defined that represents mutual information of two nodes connected by that directional edge. A fraud detection score can be defined for each survey response set based on a conformance of response values for that survey response set to the mutual information represented by the edges of the maximum weight spanning tree. A distribution of the fraud detection scores can be determined, and a subset of the survey response sets can be classified as fraudulent based on the fraud detection scores associated that subset being statistical outliers in the distribution of fraud detection scores.