Systems and methods for recommending pages
AssigneeFacebook, Inc.
InventorsBradley Ray Green, Jason Brewer
Life of this patent
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Abstract
Systems, methods, and non-transitory computer-readable media can determine a respective embedding for each entity in a set of entities that are accessible through the social networking system, wherein each embedding is learned based at least in part on one or more sessions of connections formed between users and entities of the social networking system. One or more candidate entities that are related to a first entity can be determined based at least in part on the respective embeddings for the candidate entities and the first entity. At least a first candidate entity from the one or more candidate entities can be provided as a recommendation to a user that formed a connection with the first entity.
Claims20
A computer-implemented method comprising:
- determining, by a social networking system, a respective embedding for each entity in a set of entities that are accessible through the social networking system, wherein each embedding is learned based at least in part on one or more sessions of connections formed between users and entities of the social networking system, wherein an embedding for an entity is a numerical representation of the entity, wherein the determining the respective embedding further comprises:
- determining a set of sessions from at least one sequence of connections formed between users and entities of the social networking system;
- and
- training at least one model based at least in part on the set of sessions, wherein entity connections that are formed closer in time are selected more frequently for training than entity connections that are formed further in time;
- determining, by the social networking system, one or more candidate entities that are related to a first entity based at least in part on the respective embeddings for the candidate entities and the first entity;
- and
- providing, by the social networking system, at least a first candidate entity from the one or more candidate entities as a recommendation to a user that formed a connection with the first entity.
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:
- determining a respective embedding for each entity in a set of entities that are accessible through a social networking system, wherein each embedding is learned based at least in part on one or more sessions of connections formed between users and entities of the social networking system, wherein an embedding for an entity is a numerical representation of the entity, wherein the determining the respective embedding further comprises:
- determining a set of sessions from at least one sequence of connections formed between users and entities of the social networking system;
- and
- training at least one model based at least in part on the set of sessions, wherein entity connections that are formed closer in time are selected more frequently for training than entity connections that are formed further in time;
- determining one or more candidate entities that are related to a first entity based at least in part on the respective embeddings for the candidate entities and the first entity;
- and
- providing at least a first candidate entity from the one or more candidate entities as a recommendation to a user that formed a connection with the first entity.
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:
- determining a respective embedding for each entity in a set of entities that are accessible through a social networking system, wherein each embedding is learned based at least in part on one or more sessions of connections formed between users and entities of the social networking system, wherein an embedding for an entity is a numerical representation of the entity, wherein the determining the respective embedding further comprises:
- determining a set of sessions from at least one sequence of connections formed between users and entities of the social networking system;
- and
- training at least one model based at least in part on the set of sessions, wherein entity connections that are formed closer in time are selected more frequently for training than entity connections that are formed further in time;
- determining one or more candidate entities that are related to a first entity based at least in part on the respective embeddings for the candidate entities and the first entity;
- and
- providing at least a first candidate entity from the one or more candidate entities as a recommendation to a user that formed a connection with the first entity.
Dependencies are inferred from the claim text.