Contextual set selection

A system, comprising:

• a processor configured to:
• provide an initial list of candidate items automatically evaluated and chosen for an end-user;
• receive a selection of one or more items in the initial list of candidate items from an expert user different than the end-user to include in an item group set for the end-user;
• evaluate eligible items to identify an additional item to include in the item group set based at least in part on an expert judgment prediction machine learning model trained to predict based at least in part on the one or more items already in the item group set a likelihood of a certain item being evaluated would be selected for inclusion in the item group set, wherein the expert judgment prediction machine learning model is trained in part by using previous item selections by experts to predict items likely to be selected by an expert for different types of end-users;
• based on the evaluation, include the additional item in the item group set;
• indicate member items in the item group set;
• receive from the expert user feedback regarding the member items in the item group set;
• and
• retrain the expert judgment prediction machine learning model based on the expert user feedback;
• and
• a memory coupled to the processor and configured to provide the processor with instructions.

A computer program product, the computer program product being embodied in a non-transitory computer readable storage medium and comprising computer instructions for:

• providing an initial list of candidate items automatically evaluated and chosen for an end-user;
• receiving a selection of one or more items in the initial list of candidate items from an expert user different than the end-user to include in an item group set for the end-user;
• evaluating eligible items to identify an additional item to include in the item group set based at least in part on an expert judgment prediction machine learning model trained to predict based at least in part on the one or more items already in the item group set a likelihood of a certain item being evaluated would be selected for inclusion in the item group set, wherein the expert judgment prediction machine learning model is trained in part by using previous item selections by experts to predict items likely to be selected by an expert for different types of end-users;
• based on the evaluation, including the additional item in the item group set;
• indicating member items in the item group set;
• receiving from the expert user feedback regarding the member items in the item group set;
• and
• retraining the expert judgment prediction machine learning model based on the expert user feedback.