公开(公告)号：US20200053178A1

公开(公告)日：2020-02-13

申请号：US16660701

申请日：2019-10-22

Applicant: Facebook, Inc.

Inventor： Leif Erik Foged ,  Shaun Patric Allison

IPC: H04L29/08 ,  H04L12/58

Abstract: A method may include one or more computing devices receiving an indication that a triggering action has been detected from a client device, identifying one or more notifications associated with the triggering action, wherein the one or more notifications have been stored in a queue prior to receiving the indication that the triggering action has been detected, and, for each of the one or more identified notifications, calculating a click-through probability that a user associated with the client device will interact with the notification, wherein the click-through probability is calculated based at least in part on a period the notification was stored in the queue prior to receiving the indication that the of the triggering action has been detected, and determining whether the calculated click-through probability satisfies a threshold and sending, in response to determining that the calculated click-through probability satisfies the threshold, the identified notification to the client device.

公开(公告)号：US20180027092A1

公开(公告)日：2018-01-25

申请号：US15215922

申请日：2016-07-21

Applicant: Facebook, Inc.

Inventor： Leif Erik Foged ,  Shaun Patric Allison

IPC: H04L29/08 ,  G06N7/00 ,  G06N99/00

CPC classification number: H04L67/327 ,  G06N3/0427 ,  G06N3/08 ,  G06N5/022 ,  G06N20/00 ,  H04L67/22 ,  H04L67/306

Abstract: In one embodiments, one or more computer systems receive, from a client device of a user, a request to access content. The computer systems access a plurality of assets representing the content. The computer devices calculate, for each asset, using a deep-learning model, a probability of an interaction by the user upon providing the asset to the user, wherein the deep-learning model is based at least in part on one or more features associated with the user, the asset, or the content. The computer devices selects one of the assets based on the probability. The computer devices send, to the client device, the selected asset.

公开(公告)号：US11019177B2

公开(公告)日：2021-05-25

申请号：US15215922

申请日：2016-07-21

Applicant: Facebook, Inc.

Inventor： Leif Erik Foged ,  Shaun Patric Allison

IPC: G06N20/00 ,  G06N5/02 ,  G06N3/04 ,  G06N3/08 ,  H04L29/08

Abstract: In one embodiments, one or more computer systems receive, from a client device of a user, a request to access content. The computer systems access a plurality of assets representing the content. The computer devices calculate, for each asset, using a deep-learning model, a probability of an interaction by the user upon providing the asset to the user, wherein the deep-learning model is based at least in part on one or more features associated with the user, the asset, or the content. The computer devices selects one of the assets based on the probability. The computer devices send, to the client device, the selected asset.

公开(公告)号：US10819812B2

公开(公告)日：2020-10-27

申请号：US16660701

申请日：2019-10-22

Applicant: Facebook, Inc.

Inventor： Leif Erik Foged ,  Shaun Patric Allison

IPC: H04L29/08 ,  H04L12/58 ,  G06N20/00 ,  G06N5/00 ,  G06N5/02

Abstract: A method may include one or more computing devices receiving an indication that a triggering action has been detected from a client device, identifying one or more notifications associated with the triggering action, wherein the one or more notifications have been stored in a queue prior to receiving the indication that the triggering action has been detected, and, for each of the one or more identified notifications, calculating a click-through probability that a user associated with the client device will interact with the notification, wherein the click-through probability is calculated based at least in part on a period the notification was stored in the queue prior to receiving the indication that the of the triggering action has been detected, and determining whether the calculated click-through probability satisfies a threshold and sending, in response to determining that the calculated click-through probability satisfies the threshold, the identified notification to the client device.

公开(公告)号：US20180013844A1

公开(公告)日：2018-01-11

申请号：US15205322

申请日：2016-07-08

Applicant: Facebook, Inc.

Inventor： Leif Erik Foged ,  Shaun Patric Allison

IPC: H04L29/08 ,  H04L12/58 ,  G06N99/00 ,  H04L29/06 ,  G06N7/00

CPC classification number: H04L67/22 ,  G06N5/003 ,  G06N5/025 ,  G06N20/00 ,  H04L51/24 ,  H04L51/32 ,  H04L67/02

Abstract: In one embodiment, a method includes one or more computing devices detecting a triggering action by a user of a social-networking system, wherein the detecting includes receiving information about the triggering action from a client device associated with the user and accessing a queue including multiple notifications. The method also includes, for each of one or more of the notifications, calculating using a machine-learning model, a click-through probability that the user will interact with the notification upon display of the notification, wherein the machine-learning model is based at least in part on one or more features associated with the user or the notification, determining whether the click-through probability satisfies a threshold, and if the click-through probability satisfies the threshold, then sending the notification to the client device associated with the user for display, else, removing the notification from the queue.