Dynamically generating recommendations based on social graph information
US-9223879-B2 · Dec 29, 2015 · US
US9602965B1 · US · B1
| Field | Value |
|---|---|
| Publication number | US-9602965-B1 |
| Application number | US-201514935263-A |
| Country | US |
| Kind code | B1 |
| Filing date | Nov 6, 2015 |
| Priority date | Nov 6, 2015 |
| Publication date | Mar 21, 2017 |
| Grant date | Mar 21, 2017 |
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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.
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What is claimed is: 1. A method comprising, 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; identifying a plurality of candidate place-entities associated with the online social network that correspond to the geographic-location information, wherein each candidate place-entity is associated with a particular geographic location; 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, wherein the confidence score represents a probability that the first user is located at the candidate place-entity; and 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. 2. The method of claim 1 , wherein the geographic-location information comprises a latitude-longitude pair determined based on one or more signals received by the mobile-client system. 3. The method of claim 2 , wherein the geographic-location information further comprises an accuracy value associated with the latitude-longitude pair. 4. The method of claim 1 , wherein the geographic-location information comprises signal-information associated with one or more signals received by the mobile-client system, the signals comprising a Global Positioning System (GPS) signal, a Wi-Fi signal, a BLUETOOTH signal, a cellular signal, or a near field communication (NFC) signal. 5. The method of claim 4 , wherein the signal-information comprises a signal strength of one of the signals or an identifier of a device that sent one of the signals. 6. The method of claim 1 , wherein the geographic-location information comprises a check-in via the online social network by the first user. 7. The method of claim 1 , wherein the particular geographic location associated with each identified candidate place-entity is within a threshold distance of a geographic location of the mobile-client system. 8. The method of claim 1 , further comprising accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, wherein the first user corresponds to a first node in the social graph and the plurality of candidate place-entities corresponds to a plurality of second nodes in the social graph, respectively. 9. The method of claim 8 , wherein the confidence score is further based on social-graph information associated with the first user. 10. The method of claim 8 , wherein the confidence score is further based on social-graph information associated with a second user of the online social network, the second user being within a threshold degree of separation from the first user. 11. The method of claim 1 , wherein: the location-probability distribution associated with the candidate place-entity comprises a point, the point corresponding to the particular geographic location of the candidate place-entity; and the confidence score is further based on a distance between the point and a geographic location of the mobile-client system. 12. The method of claim 1 , wherein: the location-probability distribution associated with the candidate place-entity comprises a power-law distribution centered at a point, the point corresponding to the particular geographic location of the candidate place-entity; and the confidence score is further based on a value of the power-law distribution at a geographic location of the mobile-client system. 13. The method of claim 1 , wherein: the location-probability distribution associated with the candidate place-entity comprises a kernel density estimate corresponding to a probability density associated with the candidate place-entity; and the confidence score is further based on a value of the kernel density estimate at a geographic location of the mobile-client system. 14. The method of claim 1 , wherein: the location-probability distribution associated with the candidate place-entity comprises a polygon representing a shape of the candidate place-entity; and the confidence score is further based on a geographic location of the mobile-client system with respect to the polygon. 15. The method of claim 1 , further comprising: receiving, from the mobile-client system of the first user, a selection of one of the candidate place-entities sent to the mobile-client system of the first user; and recalculating, based on the received selection, the location-probability distribution associated with one or more of the candidate place-entities sent to the mobile-client system of the first user. 16. The method of claim 1 , further comprising: receiving a plurality of new geographic-location information associated with a new place-entity, the new geographic-location information sent by a respective plurality of other mobile-client systems associated with a respective plurality of other users of the online social network; generating, in a social graph, a new social-graph node corresponding to the new place-entity, the social graph comprising a plurality of nodes and a plurality of edges connecting the nodes; and creating an edge between the new social-graph node and each node associated with each of the plurality of other users. 17. The method of claim 1 , wherein the information sent to the mobile-client system of the first user comprises an advertisement associated with one of the candidate place-entities having the confidence score above the threshold confidence score. 18. The method of claim 1 , wherein the information sent to the mobile-client system of the first user comprises a suggestion to the first user to perform an action associated with one of the one or more candidate place-entities. 19. One or more computer-readable non-transitory storage media embodying software that is operable when executed to: receive, from a mobile-client system of a first user of an online social network, geographic-location information associated with the mobile-client system; identify a plurality of candidate place-entities associated with the online social network that correspond to the geographic-location information, wherein each candidate place-entity is associated with a particular geographic location; determine, 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, wherein the confidence score represents a probability that the first user is located at the candidate place-entity; and send, 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. 20. A system comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to: receive, from a mobile-client system of a first user of an online social network, geographic-location information associated with the mobile-client system; identify a plurality of candidate place-entities associated with the online s
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