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

Claim 0:
1. A computer-implemented method for recommending digital content by a recommendation system, the method comprising:
determining, by a processor, user preferences of a given user and a time horizon indicating how familiar the recommendation system is with the given user;
determining, by the processor, a group for the given user based on the determined user preferences;
determining, by the processor, a number of users of the determined group and a similarity of the given user to the determined group;
applying, by the processor, the number of users, the similarity, and the time horizon to a model selection classifier to select one of a personalized model of the given user and a group model of the determined group; and
running, by the processor, the selected model to determine digital content to recommend to the given user,
wherein prior to the running, the processor trains the model selection classifier by:
generating a sample comprising a number of sample users and a number of iterations I;
for each of I users of the sample users, simulating 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, simulating 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
labeling 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 labeling the sample to indicate the personalized model.