公开(公告)号：US20180276544A1

公开(公告)日：2018-09-27

申请号：US15468874

申请日：2017-03-24

Applicant: Facebook, Inc.

Inventor： Tanmoy Chakraborty ,  Lei Wang ,  Manas Somaiya ,  Patrick Edward Bozeman

IPC: G06N5/02 ,  G06F17/30

Abstract: An online system generates one or more models that determine a likelihood of a user interacting with an application over a particular time interval after installing the application. To generate the one or more models, the online system obtains information describing a user's interaction with the application that occurred greater than a threshold time period prior to a time for which user interaction with the application is to be determined. Example user interactions with the application include: usage of the application, numbers of particular interactions with the application, an amount of compensation the application receives from the user, interactions with other users of the application via the application, and any other suitable interactions. Various engagement metrics may be predicted by the one or more models such as an amount of time spent using the application, particular actions taken in the application, and revenue generated by the user in the application.

公开(公告)号：US10755180B2

公开(公告)日：2020-08-25

申请号：US15468874

申请日：2017-03-24

Applicant: Facebook, Inc.

Inventor： Tanmoy Chakraborty ,  Lei Wang ,  Manas Somaiya ,  Patrick Edward Bozeman

IPC: G06N5/02 ,  G06F16/9535 ,  H04L29/08 ,  G06Q30/02

Abstract: An online system generates one or more models that determine a likelihood of a user interacting with an application over a particular time interval after installing the application. To generate the one or more models, the online system obtains information describing a user's interaction with the application that occurred greater than a threshold time period prior to a time for which user interaction with the application is to be determined. Example user interactions with the application include: usage of the application, numbers of particular interactions with the application, an amount of compensation the application receives from the user, interactions with other users of the application via the application, and any other suitable interactions. Various engagement metrics may be predicted by the one or more models such as an amount of time spent using the application, particular actions taken in the application, and revenue generated by the user in the application.