Grouping Categorical Anomalies

We present an approach for discovery of groups of unusual data points that are anomalous for similar reasons. This differs from clustering in that the points that are grouped may be quite 'distant' and can use categorical attributes, and differs from anomaly detection in that we are not looking for individual outliers.