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：US20190130444A1

公开(公告)日：2019-05-02

申请号：US15802335

申请日：2017-11-02

Applicant: Facebook, Inc.

Inventor： Zhiye Fei ,  Manas Somaiya ,  Tanmoy Chakraborty ,  Lei Wang ,  Taedong Kim

IPC: G06Q30/02 ,  G06F15/18 ,  G06F17/30

Abstract: Methods and systems are described herein for predicting the quality of content items for display to a user of an online system. The method involves training a model to predict user values for content items based on ratings provided by a panel of professional raters for a set of content items. The trained model receives embeddings for a viewing user of the online system and for a page associated with a content item along with edge factors representing the viewing user's interactions on the online system and generates a user value representing the predicted quality of the content item for the viewing user. The method further involves combining the predicted user value with a user interaction score for the content item to generate a content item score used to determine whether to display the content item to the viewing user.

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.