Content recommendations based upon historical future data
AssigneeOath Inc.
InventorsRoie Melamed, Yohay Kaplan, Yair Koren
Life of this patent
Estimating the term…
Abstract
One or more computing devices, systems, and/or methods for content recommendations using historical future data are provided. A model serving delay time is computed as an average of training delays of events. A historical data time interval is determined based upon the model serving delay time. A model is trained for predicting user content preferences using historic user distribution data and historic content distribution data associated with the historic data time interval. The model is utilized to generate and provide content recommendations to users.
Claims20
A method, comprising:
- executing, on a processor of a computing device, instructions that cause the computing device to perform operations, the operations comprising:
- computing a model serving delay time as an average of training delays of events, wherein a training delay corresponds to a difference between an event serve time of an event and a train time of a model that served a recommendation associated with the event;
- in response to determining that a current day occurs within a set of weekdays, determining a historical data time interval as a day prior to the current day plus the model serving delay time;
- training the model for predicting user content preferences using historic user distribution data and historic content distribution data associated with the historical data time interval;
- and
- utilizing the model to generate and provide a content recommendation for a user.
A computing device comprising:
- a processor;
- and
- memory comprising processor-executable instructions that when executed by the processor cause performance of operations, the operations comprising:
- computing a model serving delay time as an average of training delays of events, wherein a training delay corresponds to a difference between an event serve time of an event and a train time of a model that served a recommendation associated with the event;
- in response to determining that a current day is a weekend day, determining a historical data time interval as a week prior to the current day plus the model serving delay time;
- training the model for predicting user content preferences using historic user distribution data and historic content distribution data associated with the historical data time interval;
- and
- utilizing the model to generate and provide a content recommendation for a user.
A non-transitory machine readable medium having stored thereon processor-executable instructions that when executed cause performance of operations, the operations comprising:
- computing a model serving delay time as an average of training delays of events, wherein a training delay corresponds to a difference between an event serve time of an event and a train time of a model that served a recommendation associated with the event;
- in response to determining that a current day is a weekend day that does not occur within a set of weekdays, determining a historical data time interval as a plurality of days prior to the current day plus the model serving delay time;
- training the model for predicting user content preferences using historic user distribution data and historic content distribution data associated with the historical data time interval;
- and
- utilizing the model to generate and provide a content recommendation for a user.
Dependencies are inferred from the claim text.