Facebook, Inc.

Jan Kalis

Justin Moore

Aaron Bryan Adcock

Jan Kodovsky

Danielle Rothermel

Zhong Wang

Robert James Sicurelli, Iii

Lars Seren Backstrom

Fei Huang

Thomas Frederick Dimson

Taylor Gordon

Long Chen

In one embodiment, a method includes receiving, by one or more computing devices of an online social network, from a client system of a first user of the online social network, a query inputted by the first user. The method further includes accessing a social graph of the online social network, the social graph including multiple nodes and multiple edges connecting the nodes, each node corresponding to an entity associated with the online social network. The method also includes identifying multiple entities matching the query, each identified entity having a duplication-value with respect to a canonical-entity, the duplication-values being based on a name similarity between the identified entity and the canonical-entity. The method also includes suppressing one or more entities of the identified entities based on the duplication-value of the entity and social-graph information associated with the entity.

Suppressing entity suggestions on online social networks

Systems, methods, and non-transitory computer-readable media can generate a set of candidate content items from a plurality of content items that are available in the social networking system for a first user. A corresponding score for each of the candidate content items can be generated based at least in part on one or more social affinity coefficients corresponding to the first user and a respective second user associated with a candidate content item, wherein a social affinity coefficient provides a quantitative measurement of the strength of a relationship between two users. A first set of content items from the set of candidate content items can be determined based at least in part on the respective scores, wherein content items in the first set are included in a content feed provided to the first user.

Systems and methods for providing content

In one embodiment, a method includes, by one or more computing devices of an online social network, receiving comparison information associated with two or more particular place-entities from a client system of a first user of the online social network, each particular place-entity being associated with a particular score on a first scoring scale and a first feature, ranking a scored list of place-entities comprising at least the two or more particular place-entities associated with the online social network based in part on the comparison information, wherein each place-entity of the scored list is associated with a score on the first scoring scale, and determining a place-classifier algorithm based at least in part on the ranked list of place-entities and one or more features associated with each place-entity of the ranked list, the one or more features comprising at least the first feature.

Ranking of place-entities on online social networks

In one embodiment, a method includes sending information associated with multiple candidate place-entities to a user, receiving a selection of one candidate place-entity by the user, and updating the rating of the selected candidate place-entity on an online social network. In particular, the sending is based on calculated probabilities the candidate place-entities are associated with a particular geographic location.

Location-based place determination using online social networks

In one embodiment, a method includes, by one or more computing devices of an online social network, sending, to a client system of a first user of the online social network, a first request to compare two or more place-entities associated with the online social network, where the first user is connected to each place-entity within a social graph of the online social network, each place-entity being associated with a particular score on a first scoring scale and a first feature. The method further includes receiving, from the client system, comparison information responsive to the first request, the comparison information indicating an ordered ranking of the two or more place-entities. The method also includes accessing a scored list of place-entities associated with the online social network, where the scored list is based on scores on the first scoring scale for the place-entities.

In one embodiment, one or more computing devices of an online social network, receives, from a mobile-client system, geographic-location information associated with the mobile-client system. The one or more computing devices identify multiple candidate place-entities associated with the online social network that correspond to the geographic-location information, where each candidate place-entity is associated with a particular geographic location. The method also includes determining, for each candidate place-entity, a confidence score based on the geographic-location information associated with the mobile-client system, where the confidence score represents a probability that the first user is located at the candidate place-entity. A location-probability distribution associated with the candidate place-entity can also be used to calculate the confidence score. The one or more computing devices send, to the mobile-client system, information associated with one or more of the candidate place-entities based on their respective confidence scores.

In one embodiment, a method includes, by one or more computing devices of an online social network, receiving, from a mobile-client system of a first user of the online social network, geographic-location information associated with the mobile-client system. The method further includes identifying multiple candidate place-entities associated with the online social network that correspond to the geographic-location information, where each candidate place-entity is associated with a particular geographic location. The method also includes determining, for each candidate place-entity, a confidence score based on the geographic-location information associated with the mobile-client system and a location-probability distribution associated with the candidate place-entity, where the confidence score represents a probability that the first user is located at the candidate place-entity. The method also includes sending, to the mobile-client system of the first user, information associated with one or more of the candidate place-entities having a confidence score above a threshold confidence score.

Growing community of inventors

New York, NY, United States of America

Jan Kalis