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

Claim 10:
11. A training system for training a recommendation system, comprising:
a memory storing a computer program for training a learning agent and deploying the learning agent to the recommendation system;
a network interface for communicating with a computer network; and
a processor configured to execute the computer program,
wherein the computer program is configured to train the learning agent to select between a group model for a given user and a personalized model for the given user based on a number of first users of a group associated with the given user, a similarity of the given user to the group, and a time horizon indicating how familiar the recommendation system is with the given user to recommend digital content, and
wherein the computer program is further configured to output the learning agent across the computer network to a device housing the recommendation system,
wherein the computer program trains the learning agent 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.