Location-Based Place Determination Using Online Social Networks

• US 20170156033A1
• Filed: 02/14/2017
• Published: 06/01/2017
• Est. Priority Date: 11/06/2015
• Status: Active Grant

• Current Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Original Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Inventors: Adcock, Aaron Bryan, Rothermel, Danielle, Wang, Zhong, Kalis, Jan, Moore, Justin, Kodovsky, Jan
• Granted Patent: US 10,003,922 B2
• Time in Patent Office: Days
• CPC Class Codes: H04L 51/52 for supporting social networking services
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/023 using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
• CPC Class Codes: H04W 4/029 Location-based management or tracking services

Abstract

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.

Claims

1. A method comprising, by one or more computing devices:

receiving, from a mobile-client system, geographic-location information associated with the mobile-client system;

calculating, for each of a plurality of candidate place-entities corresponding to the geographic-location information, a confidence score based on the geographic-location information, wherein the confidence score represents a probability that the mobile-client system is located at the candidate place-entity; and

sending, to the mobile-client system, information associated with one or more of the candidate place-entities based on their respective confidence scores.

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 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.

4. The method of claim 3, 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.

5. The method of claim 1, wherein the geographic-location information comprises a check-in via the online social network by a first user of the mobile-client system.

6. 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.

7. 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 a first user of the mobile-client system 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.

8. The method of claim 7, wherein the confidence score is further based on social-graph information associated with the first user.

9. The method of claim 7, 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.

10. The method of claim 1, wherein the confidence score is further based on a location-probability distribution associated with the candidate place-entity.

11. The method of claim 10, 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 10, 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 10, 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 10, 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 10, further comprising:

receiving, from the mobile-client system, a user selection of one of the candidate place-entities sent to the mobile-client system; 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.

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 comprises an advertisement associated with one of the candidate place-entities based on its respective confidence score.

18. The method of claim 1, wherein the information sent to the mobile-client system comprises a suggestion to a first user of the mobile-client system 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, geographic-location information associated with the mobile-client system;

calculate, for each of a plurality of candidate place-entities corresponding to the geographic-location information, a confidence score based on the geographic-location information, wherein the confidence score represents a probability that the mobile-client system is located at the candidate place-entity; and

send, to the mobile-client system, information associated with one or more of the candidate place-entities based on their respective confidence scores.

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, geographic-location information associated with the mobile-client system;

calculate, for each of a plurality of candidate place-entities corresponding to the geographic-location information, a confidence score based on the geographic-location information, wherein the confidence score represents a probability that the mobile-client system is located at the candidate place-entity; and

send, to the mobile-client system, information associated with one or more of the candidate place-entities based on their respective confidence scores.