Geo-locating individuals based on a derived social network

• US 10,362,124 B2
• Filed: 12/18/2018
• Issued: 07/23/2019
• 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:
  US16/224,094
• Publication Number:
  US 20190124166A1
• Time in Patent Office: 217 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 further associated with second user venue information;

calculating, at the computing device, a spatial overlap metric based on a distance 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 between the first user location information and the second user location information and a social metric indicating a strength of a social relationship between the first user and second user, the social relationship being defined at least in part by a number of times and an amount of time a 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; 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 is associated with a first latitude and longitude and the second user location information is associated with a second latitude and longitude.

3. The computerized method of claim 1, wherein:

the first user location information further includes a first user device identifier and a first user duration, the first user duration including a start time and end time corresponding to the first user being associated with the first user location information; and

the second user location information further includes a second user identifier and a second user duration, the second user duration associated with start time and end time corresponding to the second user being associated with the second user location information.

4. The computerized method of claim 3, wherein the venue correlation score is based on an amount of overlap between the first user duration and the second user duration.

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 further defined by at least one of:

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

the relationship being personal or professional.

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

a received threshold value;

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

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 further associated with second user venue information;

calculate a spatial overlap metric based on a distance 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 between the first user location information and the second user location information and a social metric indicating a strength of a social relationship between the first user and second user, the social relationship being defined at least in part by a number of times and an amount of time a 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; 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 is associated with a first latitude and longitude and the second user location information is associated with a second latitude and longitude.

10. The computing system of claim 8, wherein:

the first user location information further includes a first user device identifier and a first user duration, the first user duration including a start time and end time corresponding to the first user being associated with the first user location information; and

the second user location information further includes a second user identifier and a second user duration, the second user duration associated with start time and end time corresponding to the second user being associated with the second user location information.

11. The computing system of claim 10, wherein the venue correlation score is based on an amount of overlap between the first user duration and the second user duration.

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 further defined by at least one of:

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

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; and

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 executable instructions operable to cause an apparatus 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 further associated with second user venue information;

calculate a spatial overlap metric based on a distance 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 between the first user location information and the second user location information and a social metric indicating a strength of a social relationship between the first user and second user, the social relationship being defined at least in part by a number of times and an amount of time a 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; and

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

16. The non-transitory computer readable medium of claim 15, wherein the first user location information is associated with a first latitude and longitude and the second user location information is associated with a second latitude and longitude.

17. The non-transitory computer readable medium of claim 15, wherein:

the first user location information further includes a first user device identifier and a first user duration, the first user duration including a start time and end time corresponding to the first user being associated with the first user location information; and

the second user location information further includes a second user identifier and a second user duration, the second user duration associated with start time and end time corresponding to the second user being associated with the second user location information.

18. The non-transitory computer readable medium of claim 17, wherein the venue correlation score is based on an amount of overlap between the first user duration and the second user duration.

19. The non-transitory computer readable medium of claim 15, wherein the venue correlation score is further based on a confidence level assigned to the second user venue information.

20. The non-transitory computer readable medium of claim 15, wherein the social metric is further defined by at least one of:

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

the relationship being personal or professional.