Location Data for Defining Places and Traffic

• US 20160182424A1
• Filed: 12/18/2014
• Published: 06/23/2016
• Est. Priority Date: 12/18/2014
• Status: Active Grant

• Current Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Original Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Inventors: Maginnis, Patrick Brendan, Toksvig, Michael John McKenzie, Tseng, Erick
• Granted Patent: US 10,187,343 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: H04L 51/222 using geographical location information, e.g. messages transmitted or received in proximity of a certain spot or area
• CPC Class Codes: H04L 51/52 for supporting social networking services
• 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 4/021 Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
• CPC Class Codes: H04W 4/027 using movement velocity, acceleration information
• CPC Class Codes: H04W 4/029 Location-based management or tracking services
• CPC Class Codes: H04W 64/006 with additional information processing, e.g. for direction or speed determination

Abstract

In one embodiment, a computing device selects a number of location updates from users which corresponds to a place. Each location update includes data indicating a geographic location that a user was at, and a time corresponding to when the user was at the geographic location. The computing device selects a first subset of the location updates which have geographic locations within a particular geographic area. For each location update in the first subset, the computing device determines a corresponding user and time. The computing device selects a second subset of location updates, each location update in the second subset corresponding to a user from the first subset, and a time within a threshold time of the time of the location update in the first subset. The computing device generates a probability map based on a distribution of geographic locations corresponding to the location updates in the second subset.

Claims

1. A method comprising:

by a computing device, selecting a plurality of location updates corresponding to a place, the plurality of location updates being received from one or more users, wherein each location update comprises;

data indicating a geographic location that a user was at; and

a time stamp indicating a time when the user was at the geographic location;

by a computing device, selecting a first subset of the location updates, wherein the location updates in the first subset correspond to geographic locations within a geographic area;

by a computing device, for each of one or more of the location updates in the first subset;

determining the user corresponding to the location update; and

determining the time corresponding to the location update;

by a computing device, selecting a second subset of the location updates, wherein each of the location updates in the second subset corresponds to;

a user corresponding to a location update in the first subset; and

a time within a threshold amount of time of the time corresponding to the location update in the first subset;

by a computing device, generating a probability map based on a distribution of geographic locations corresponding to the location updates in the second subset; and

by a computing device, defining one or more boundaries corresponding to the place based at least in part on the probability map.

2. The method of claim 1, further comprising storing the one or more boundaries in one or more map data stores of a computing device.

3. The method of claim 1, wherein the geographic area of the first subset comprises a centroid region of a location distribution of geographic locations corresponding to the plurality of location updates.

4. The method of claim 3, wherein the centroid region is defined by a predetermined radius with respect to a centroid point of the location distribution.

5. The method of claim 4, wherein the centroid region is defined by a shape such that a predetermined proportion of the geographic distributions are within a predetermined distance of the centroid region.

6. The method of claim 1, wherein the plurality of location updates are received during a predetermined time period.

7. The method of claim 1, wherein each location update further comprises user information associated with the user.

8. The method of claim 7, wherein the plurality of location updates are filtered by one or more demographic characteristics of the one or more users.

9. The method of claim 1, wherein the place is a pathway.

10. The method of claim 9, wherein the plurality of location updates along a pathway are determined based on a moving speed calculated for each location update.

11. The method of claim 1, wherein the place is associated with a geographic area defined in one or more map data stores accessible by the computing device.

12. The method of claim 1, wherein the place is not associated with an geographic area defined in one or more map data stores accessible by the computing device.

13. The method of claim 12, wherein the geographic area and the place are added to one or more map data stores accessible by the computing device.

14. The method of claim 13, wherein the geographic area and the place are further associated with one or more demographic characteristics of users sending location updates from the geographic area.

15. The method of claim 13, further comprising sending a query to one or more users corresponding to location updates within the geographic area, the query comprising a request for further defining information associated with the geographic area.

16. The method of claim 1, further comprising validating the probability map based at least in part on a comparison of the probability map with the second subset of location updates.

17. The method of claim 16, wherein the probability map is adjusted based at least in part on the comparison.

18. The method of claim 16, wherein the one or more boundaries are adjusted based at least in part on the comparison.

19. One or more non-transitory, computer-readable storage media embodying software that is operable when executed to:

select a plurality of location updates corresponding to a place, the plurality of location updates being received from one or more users, wherein each location update comprises;

data indicating a geographic location that a user was at; and

a time stamp indicating a time when the user was at the geographic location;

select a first subset of the location updates, wherein the location updates in the first subset correspond to geographic locations within a geographic area;

for each of one or more of the location updates in the first subset;

determine the user corresponding to the location update; and

determine the time corresponding to the location update;

select a second subset of the location updates, wherein each of the location updates in the second subset corresponds to;

a user corresponding to a location update in the first subset; and

a time within a threshold amount of time of the time corresponding to the location update in the first subset;

generate a probability map based on a distribution of geographic locations corresponding to the location updates in the second subset; and

define one or more boundaries corresponding to the place based at least in part on the probability map.

20. A system comprising:

one or more processors; and

a memory coupled to the processors comprising instructions executable by the processors, the processors being operable when executing the instructions to;

select a plurality of location updates corresponding to a place, the plurality of location updates being received from one or more users, wherein each location update comprises;

data indicating a geographic location that a user was at; and

a time stamp indicating a time when the user was at the geographic location;

select a first subset of the location updates, wherein the location updates in the first subset correspond to geographic locations within a geographic area;

for each of one or more of the location updates in the first subset;

determine the user corresponding to the location update; and

determine the time corresponding to the location update;

select a second subset of the location updates, wherein each of the location updates in the second subset corresponds to;

a user corresponding to a location update in the first subset; and

a time within a threshold amount of time of the time corresponding to the location update in the first subset;

generate a probability map based on a distribution of geographic locations corresponding to the location updates in the second subset; and

define one or more boundaries corresponding to the place based at least in part on the probability map.