Geo-locating individuals based on a derived social network

• US 10,542,105 B2
• Filed: 06/13/2019
• Issued: 01/21/2020
• Est. Priority Date: 08/11/2016
• Status: Active Grant

• Current Assignee: Axon Vibe AG
• Original Assignee: Axon Vibe AG
• Inventors: Yoshida, Katherine, Annicq, Thomas, Oberli, Roman, Tagliabue, Jacopo
• Primary Examiner(s): Nealon, William
• Application Number:
  US16/440,052
• Publication Number:
  US 20190297153A1
• Time in Patent Office: 222 Days
• Field of Search: 4554561
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04W 4/023 using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds

Abstract

Techniques for determining a location of a user based on locations of other users. First user location information and second user location information is received. The first user location information includes a first centroid and first radius associated with a first user position and the second user location information includes a second centroid and second radius associated with a second user position. The second user is further associated with second user venue information. A venue correlation score between the first user and the second user is determined based on an amount of overlap between the first user radius and the second user radius and a social metric indicating a strength of a social relationship between the first user and second user. Venue information for the first user is created based on the second user venue information when the relationship score exceeds a threshold value.

Claims

1. A computerized method of determining a location of a user based on locations of other users, the computerized method comprising:

receiving, at a computing device, first user location information associated with a first user from a first user device;

receiving, at the computing device, second user location information associated with a second user from a second user device, the second user being associated with second user venue information;

calculating, at the computing device, a spatial overlap metric based on a correlation between the first user location information and the second user location information;

determining, at the computing device, a venue correlation score between the first user and the second user based on the spatial overlap metric and a social metric indicating a strength of a social relationship between the first user and second user; and

creating, at the computing device, venue information for the first user based on the second user venue information when the venue correlation score exceeds a threshold value.

2. The computerized method of claim 1, wherein:

the first user location information includes first geographic coordinates and the second user location information includes second geographic coordinates, and

the correlation between the first user location information and the second user location information includes a distance between the first geographic coordinates and the second geographic coordinates.

3. The computerized method of claim 1, wherein:

the first user location information includes first user temporal information identifying a first time period in which the first user is associated with the first user location information; and

the second user location information includes second user temporal information identifying a second time period in which the second user is associated with the second user location information.

4. The computerized method of claim 3, wherein the venue correlation score is further based on a second correlation between the first user temporal information and the second user temporal information.

5. The computerized method of claim 1, wherein the venue correlation score is further based on a confidence level assigned to the second user venue information.

6. The computerized method of claim 1, wherein the social metric is defined by at least one of:

a number of times the first user is in a proximate location to the second user prior to receiving the first user location information and the second user location information;

an amount of time the first user is in the proximate location to the second user prior to receiving the first user location information and the second user location information;

a length of a relationship between the first user and the second user;

or

the relationship being personal or professional.

7. The computerized method of claim 1, wherein the threshold value is based on at least one of:

a received threshold value;

a distribution of relationship scores associated with a plurality of users;

or

an application of a machine learning algorithm to a plurality of user location information and user venue information.

8. A computing system for determining a location of a user based on locations of other users, the computing system comprising:

a processor; and

a memory coupled to the processor and including computer-readable instructions that, when executed by the processor, cause the processor to;

receive first user location information associated with a first user from a first user device;

receive second user location information associated with a second user from a second user device, the second user being associated with second user venue information;

calculate a spatial overlap metric based on a correlation between the first user location information and the second user location information;

determine a venue correlation score between the first user and the second user based on the spatial overlap metric and a social metric indicating a strength of a social relationship between the first user and second user; and

create venue information for the first user based on the second user venue information when the venue correlation score exceeds a threshold value.

9. The computing system of claim 8, wherein:

the first user location information includes first geographic coordinates and the second user location information includes second geographic coordinates, and

the correlation between the first user location information and the second user location information includes a distance between the first geographic coordinates and the second geographic coordinates.

10. The computing system of claim 8, wherein the computer-readable instructions further cause the processor to:

receive first temporal information associated with the first user from the first user device; and

receive second temporal information associated with the second user from the second user device.

11. The computing system of claim 10, wherein the spatial overlap metric is further based on a second correlation between the first user temporal information and the second user temporal information.

12. The computing system of claim 8, wherein the venue correlation score is further based on a confidence level assigned to the second user venue information.

13. The computing system of claim 8, wherein the social metric is defined by at least one of:

a number of times the first user is in a proximate location to the second user prior to receiving the first user location information and the second user location information;

an amount of time the first user is in the proximate location to the second user prior to receiving the first user location information and the second user location information;

a length of a relationship between the first user and the second user;

or

the relationship being personal or professional.

14. The computing system of claim 8, wherein the threshold value is based on at least one of:

a received threshold value;

a distribution of relationship scores associated with a plurality of users;

or

an application of a machine learning algorithm to a plurality of user location information and user venue information.

15. A non-transitory computer readable medium having stored thereon computer-executable instructions that, when executed by a computing system, cause the computing system to perform a method comprising:

receiving first user location information associated with a first user from a first user device, the first user being associated with first user venue information indicating that the first user is located at one or more of a plurality of possible first venues;

receiving second user location information associated with a second user from a second user device, the second user being associated with second user venue information indicating that the second user is located at a second venue among the plurality of possible first venues;

calculating a spatial overlap metric based on a correlation between the first user location information and the second user location information;

determining a venue correlation score between the first user and the second user based on the spatial overlap metric and a social metric indicating a strength of a social relationship between the first user and second user; and

updating the first user venue information to indicate that the first user is located at the second venue when the venue correlation score exceeds a threshold value.

16. The non-transitory computer readable medium of claim 15, wherein the plurality of possible venues are located within a radius of uncertainty corresponding to the first user location information.

17. The non-transitory computer readable medium of claim 15, wherein the first user venue information is assigned a first confidence level that is below a predetermined threshold, and the second user venue information is assigned a second confidence level that exceeds the predetermined threshold.

18. The non-transitory computer readable medium of claim 15, wherein the method further comprises receiving a user verification of the second user venue information, the user verification indicating that the second user checked in at the second venue.

19. The non-transitory computer readable medium of claim 15, wherein the method further comprises receiving a third-party verification of the second user venue information.

20. The non-transitory computer readable medium of claim 19, wherein the third-party verification is indicative of a user interaction with a third party at the second venue, the user interaction including at least one of:

the second user paying for a purchase at the second venue;

or

the second user tagging a photo with the second venue.