Location-based place determination using online social networks

US9602965B1 · US · B1

Patent metadata
FieldValue
Publication numberUS-9602965-B1
Application numberUS-201514935263-A
CountryUS
Kind codeB1
Filing dateNov 6, 2015
Priority dateNov 6, 2015
Publication dateMar 21, 2017
Grant dateMar 21, 2017

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  1. Title

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  2. Abstract

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  3. Assignees and inventors

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  4. Key dates

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  5. First independent claim

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  6. CPC / IPC classifications

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  7. Citations and related patents

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Abstract

Official abstract text for this publication.

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.

First claim

Opening claim text (preview).

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

Assignees

Inventors

Classifications

  • H04W4/02Primary

    Services making use of location information · CPC title

  • Electricity · mapped topic

  • for supporting social networking services · CPC title

  • H04W4/023Primary

    using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds · CPC title

  • Location-based management or tracking services · CPC title

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What does patent US9602965B1 cover?
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…
Who is the assignee on this patent?
Facebook Inc
What technology area does this patent fall under?
Primary CPC classification H04W4/02. Mapped technology areas include Electricity.
When was this patent published?
Publication date Tue Mar 21 2017 00:00:00 GMT+0000 (Coordinated Universal Time) (B1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 11 related publications on this page (citations in our corpus or others sharing the same primary CPC).