US 11,537,911 B2 · Machine learning techniques to nurture content creation

Abstract

Techniques for nurturing content creation are provided. In one technique, a particular user is identified. Candidate entities are identified based on one or more attributes of the particular user. For each candidate entity, a feedback sensitivity measure of content creation of the candidate entity is determined. The feedback sensitivity measure is generated based on an amount of feedback, from other users, to content that the candidate entity has created. A score is then generated for the candidate entity based on the measure. A ranking of the candidate entities is determined based on the score of each candidate entity. A subset of the candidate entities is selected based on the ranking. The subset of the candidate entities is transmitted over a computer network to be presented on a computing device of the particular user.

Claims20

Dependent claims

A method comprising:

identifying a particular user;
based on one or more attributes of the particular user, identifying a plurality of entities;
for each entity in the plurality of entities:
determining a feedback sensitivity measure of content creation of the entity, wherein the feedback sensitivity measure is generated based on an amount of feedback, from other users, to content that the entity has created, and wherein generating the feedback sensitivity measure comprises using a machine-learned model to generate a first prediction of the entity creating future content given expected feedback;
generating a score for the entity based on the feedback sensitivity measure;
determining a ranking of the plurality of entities based on the score of each entity in the plurality of entities;
selecting a subset of the plurality of entities based on the ranking;
causing the subset of the plurality of entities to be presented on a computing device of the particular user;
wherein the method is performed by one or more computing devices.

6 more elements

One or more storage media storing instructions which, when executed by one or more processors, cause:

identifying a particular user;
based on one or more attributes of the particular user, identifying a plurality of entities;
for each entity in the plurality of entities:
determining a feedback sensitivity measure of content creation of the entity, wherein the feedback sensitivity measure is generated based on an amount of feedback, from other users, to content that the entity has created, and wherein generating the feedback sensitivity measure comprises using a machine-learned model to generate a first prediction of the entity creating future content given expected feedback;
generating a score for the entity based on the feedback sensitivity measure;
determining a ranking of the plurality of entities based on the score of each entity in the plurality of entities;
selecting a subset of the plurality of entities based on the ranking;
causing the subset of the plurality of entities to be presented on a computing device of the particular user.

5 more elements

A system comprising:

one or more processors;
one or more non-transitory storage media storing instructions which, when executed by one or more processors, cause:
identifying a particular user;
based on one or more attributes of the particular user, identifying a plurality of entities;
for each entity in the plurality of entities:
determining a feedback sensitivity measure of content creation of the entity, wherein the feedback sensitivity measure is generated based on an amount of feedback, from other users, to content that the entity has created, and wherein generating the feedback sensitivity measure comprises using a machine-learned model to generate a first prediction of the entity creating future content given expected feedback;
generating a score for the entity based on the feedback sensitivity measure;
determining a ranking of the plurality of entities based on the score of each entity in the plurality of entities;
selecting a subset of the plurality of entities based on the ranking;
causing the subset of the plurality of entities to be presented on a computing device of the particular user.

7 more elements

Dependencies are inferred from the claim text.

Machine learning techniques to nurture content creation

Life of this patent

Machine learning techniques to nurture content creation

Life of this patent

Abstract

Claims20