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US 2020/0401522 A1Published application
Systems and methods for providing content
AssigneeFacebook, Inc.
InventorChenyong Xu
Life of this patent
Estimating the term…
Abstract
Systems, methods, and non-transitory computer-readable media can determine that a user is interacting with a software application running on a computing device. One or more content items to be prefetched for the software application are identified based on one or more machine learning models. A request to prefetch the one or more content items for the software application is generated.
Claims22
A computer-implemented method comprising:
- training, by a computing system, a prefetch machine learning model based on training data received from a plurality of computing devices associated with a plurality of users,
- wherein the training data includes user characteristics and labeling of previous occurrences of content interaction as examples,
- wherein the user characteristics include content affinity scores determined based on an affinity machine learning model, a content affinity score being indicative of a user's predicted interest in a content item;
- determining, by the computing system, that a first user is interacting with a software application running on a computing device;
- identifying, by the computing system, one or more content items to be prefetched for the software application based on prefetch scores generated by the prefetch machine learning model, a prefetch score being indicative of a likelihood of the first user to view a content item;
- and
- generating, by the computing system, a request to prefetch the one or more content items for the software application.
4 more elements
(canceled)
(canceled)
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 a method comprising:
- training a prefetch machine learning model based on training data received from a plurality of computing devices associated with a plurality of users,
- wherein the training data includes user characteristics and labeling of previous occurrences of content interaction as examples,
- wherein the user characteristics include content affinity scores determined based on an affinity machine learning model, a content affinity score being indicative of a user's predicted interest in a content item;
- determining that a first user is interacting with a software application running on a computing device;
- identifying one or more content items to be prefetched for the software application based on prefetch scores generated by the prefetch machine learning model, a prefetch score being indicative of a likelihood of the first user to view a content item;
- and
- generating a request to prefetch the one or more content items for the software application.
7 more elements
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 prefetch machine learning model based on training data received from a plurality of computing devices associated with a plurality of users,
- wherein the training data includes user characteristics and labeling of previous occurrences of content interaction as examples,
- wherein the user characteristics include content affinity scores determined based on an affinity machine learning model, a content affinity score being indicative of a user's predicted interest in a content item;
- determining that a first user is interacting with a software application running on a computing device;
- identifying one or more content items to be prefetched for the software application based on prefetch scores generated by the prefetch machine learning model, a prefetch score being indicative of a likelihood of the first user to view a content item;
- and
- generating a request to prefetch the one or more content items for the software application.
4 more elements
Dependencies are inferred from the claim text.