ADAPTIVE GENERATION OF PERSONALIZED SCHEDULE FOR DELIVERY OF MESSAGES TO USERS USING MACHINE LEARNING MODELS
개요
발명자
William MORSE; Gunther HAVEL; Sudheer GUTTIKONDA; Chenxin TAN
IPC 분류
CPC 분류
Aspects of the present disclosure are directed to systems and methods of dynamically generating individualized or personalized times for providing messages over networked environments. The computing system may obtain, for a user device, an event dataset identifying a plurality of interaction times corresponding to a plurality of interactions over an instant time window by a user with an application on the user device to address a condition of the user. The computing system may apply the event dataset to a machine learning (ML) model. The computing system may generate based on applying the event dataset to the ML model, a defined time at which a message is to be provided to the user device during a subsequent time window. The computing system may provide for presentation on the user device to address the condition of the user, the message in accordance with the defined time.
원문 (중국어)
Aspects of the present disclosure are directed to systems and methods of dynamically generating individualized or personalized times for providing messages over networked environments. The computing system may obtain, for a user device, an event dataset identifying a plurality of interaction times corresponding to a plurality of interactions over an instant time window by a user with an application on the user device to address a condition of the user. The computing system may apply the event dataset to a machine learning (ML) model. The computing system may generate based on applying the event dataset to the ML model, a defined time at which a message is to be provided to the user device during a subsequent time window. The computing system may provide for presentation on the user device to address the condition of the user, the message in accordance with the defined time.