US Patent 11893772 Artificial intelligence system with iterative two-phase active learning

Learning iterations, individual ones of which include a respective bucket group selection phase and a class boundary refinement phase, are performed using a source data set whose records are divided into buckets. In the bucket group selection phase of an iteration, a bucket is selected for annotation based on output obtained from a classification model trained in the class boundary refinement phase of an earlier iteration. In the class boundary refinement phase, records of buckets annotated as positive-match buckets for a target class in the bucket group selection phase are selected for inclusion in a training set for a new version of the model using a model enhancement criterion. The trained version of the model is stored.