Patent ID: 11948095
Assignee: ADOBE INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 15:
16. A computer program product for training a model selection classifier to choose between selecting a group model and a personalized model for recommending digital content, the computer program product being tangibly embodied on a non-transitory computer-readable storage medium and comprising instructions that, when executed by at least one computing device, are configured to cause the at least one computing device to:
generate a sample comprising a number of sample users and a number of iterations I;
for each of I users of the sample users, simulate the corresponding sample user selecting zero or more items from a part of the digital content suggested by the group model to determine a group reward;
for each of the I users, simulate the corresponding sample user selecting zero or more items from a part of the digital content suggested by the personalized model to determine a personalized reward; and
label the sample to indicate the group model when a sum of the group rewards is greater than or equal to a sum of the personalized rewards, and otherwise label the sample to indicate the personalized model,
wherein application of a number of users of a group associated with a given user, a similarity of the given user to the group, and a time horizon indicating how familiar a recommendation system is with the given user to the model selection classifier causes selection of one of the group model and the personalized model to recommend of at least one item of the digital content.