Systems and methods for suggesting content

Patent metadata

Field	Value
Publication number	US-2018101774-A1
Application number	US-201615289781-A
Country	US
Kind code	A1
Filing date	Oct 10, 2016
Priority date	Oct 10, 2016
Publication date	Apr 12, 2018
Grant date	—

Abstract

Systems, methods, and non-transitory computer-readable media can train a machine learning model to output respective scores for content items based at least in part on information describing a user, wherein a score for a content item measures a likelihood that the user will select the content item to be included in a social profile of the user. A determination is made that a first user of the social networking system is eligible for a content item suggestion. A first content item to be provided as a suggestion to the first user is determined based at least in part on the model. The first content item is provided as a suggestion to the first user for use in a social profile of the first user.

First claim

What is claimed is:

1 . A computer-implemented method comprising:
training, by a social networking system, a machine learning model to output respective scores for content items based at least in part on information describing a user, wherein a score for a content item measures a likelihood that the user will select the content item to be included in a social profile of the user; determining, by the social networking system, that a first user of the social networking system is eligible for a content item suggestion; determining, by the social networking system, a first content item to be provided as a suggestion to the first user based at least in part on the model; and providing, by the social networking system, the first content item as a suggestion to the first user for use in a social profile of the first user.

2 . The computer-implemented method of claim 1 , wherein determining that the first user of the social networking system is eligible for a content item suggestion further comprises:
determining, by the social networking system, that the first user has not selected a cover photo for use in the social profile of the first user.

3 . The computer-implemented method of claim 1 , wherein determining that the first user of the social networking system is eligible for a content item suggestion further comprises:
determining, by the social networking system, that the first user has uploaded a content item to the social networking system.

4 . The computer-implemented method of claim 1 , wherein training the model further comprises:
generating, by the social networking system, a set of training examples that each include information describing a user and a corresponding set of features that describe a cover photo being used in a social profile of the user.

5 . The computer-implemented method of claim 4 , wherein generating the set of training examples further comprises:
determining, by the social networking system, one or more sets of words that describe a user from content that was published by the user through the social networking system.

6 . The computer-implemented method of claim 5 , wherein determining the one or more sets of words further comprises:
extracting, by the social networking system, at least one noun, verb, or concept from the content that was published by the user.

7 . The computer-implemented method of claim 4 , wherein generating the set of training examples further comprises:
determining, by the social networking system, one or more sets of words that describe a user from images that are associated with the user in the social networking system.

8 . The computer-implemented method of claim 1 , wherein determining the first content item to be provided as a suggestion to the first user further comprises:
determining, by the social networking system, respective scores for a set of content items based at least in part on the model, wherein the set of content items includes the first content item; and determining, by the social networking system, that the first content item has a highest score among the set of content items.

9 . The computer-implemented method of claim 8 , wherein the scores are adjusted based at least in part on a temporal degradation function.

10 . The computer-implemented method of claim 8 , wherein the set of content items includes content items that were uploaded to the social networking system by the first user.

11 . A system comprising:
at least one processor; and a memory storing instructions that, when executed by the at least one processor, cause the system to perform:
training a machine learning model to output respective scores for content items based at least in part on information describing a user, wherein a score for a content item measures a likelihood that the user will select the content item to be included in a social profile of the user;
determining that a first user of the social networking system is eligible for a content item suggestion;
determining a first content item to be provided as a suggestion to the first user based at least in part on the model; and
providing the first content item as a suggestion to the first user for use in a social profile of the first user.

12 . The system of claim 11 , wherein determining that the first user of the social networking system is eligible for a content item suggestion further causes the system to perform:
determining that the first user has not selected a cover photo for use in the social profile of the first user.

13 . The system of claim 11 , wherein determining that the first user of the social networking system is eligible for a content item suggestion further causes the system to perform:
determining that the first user has uploaded a content item to the social networking system.

14 . The system of claim 11 , wherein training the model further causes the system to perform:
generating a set of training examples that each include information describing a user and a corresponding set of features that describe a cover photo being used in a social profile of the user.

15 . The system of claim 14 , wherein generating the set of training examples further causes the system to perform:
determining one or more sets of words that describe a user from content that was published by the user through the social networking system.

16 . A non-transitory computer-readable storage medium including instructions that, when executed by at least one processor of a computing system, cause the computing system to perform a method comprising:
training a machine learning model to output respective scores for content items based at least in part on information describing a user, wherein a score for a content item measures a likelihood that the user will select the content item to be included in a social profile of the user; determining that a first user of the social networking system is eligible for a content item suggestion; determining a first content item to be provided as a suggestion to the first user based at least in part on the model; and providing the first content item as a suggestion to the first user for use in a social profile of the first user.

17 . The non-transitory computer-readable storage medium of claim 16 , wherein determining that the first user of the social networking system is eligible for a content item suggestion further causes the computing system to perform:
determining that the first user has not selected a cover photo for use in the social profile of the first user.

18 . The non-transitory computer-readable storage medium of claim 16 , wherein determining that the first user of the social networking system is eligible for a content item suggestion further causes the computing system to perform:
determining that the first user has uploaded a content item to the social networking system.

19 . The non-transitory computer-readable storage medium of claim 16 , wherein training the model further causes the computing system to perform:
generating a set of training examples that each include information describing a user and a corresponding set of features that describe a cover photo being used in a social profile of the user.

20 . The non-transitory computer-readable storage medium of claim 16 , wherein generating the set of training examples further causes the computing system to perform:
determining one or more sets of words that describe a user from content that was published by the user through the social networking system.

Assignees

• Facebook Inc

Inventors

• Werris Ian

Classifications

• H04W4/80

  Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication · CPC title

• G06N20/00 Primary

  Machine learning · CPC title

• G06N5/04 Primary

  Inference or reasoning models · CPC title

• H04L67/306

  User profiles · CPC title

• G06N99/005

  Physics · mapped topic