Determining locations of interest based on user visits

Patent metadata

Field	Value
Publication number	US-11669864-B2
Application number	US-201916710415-A
Country	US
Kind code	B2
Filing date	Dec 11, 2019
Priority date	Apr 27, 2007
Publication date	Jun 6, 2023
Grant date	Jun 6, 2023

Abstract

Techniques are described for determining locations of interest based on user visits. In some situations, the techniques include obtaining information about actual locations of users at various times, and automatically analyzing the information to determine particular locations in a geographic area that are of interest, such as for frequent destinations visited by users. After determining a particular location of interest, it may be represented by generating a corresponding location model to describe the geographic subarea or other location point(s) covered by the determined location of interest, and one or more points of interest (e.g., businesses, parks, schools, landmarks, etc.) may be identified that are located at or otherwise correspond to the determined location of interest. In addition, a determined location of interest may be further used in various ways, including to identify later user visits to that location (e.g., to a point of interest identified for the location).

First claim

What is claimed is:

1. A system, comprising one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to:
train a location model based on a first training dataset that comprises location information associated with a geographic location;
receive, from one or more global positioning system (GPS) receivers, location information associated with one or more mobile devices in a spatial radius with respect to the geographic location over a period of time;
calculate location invariance measures with respect to the spatial radius over the period of time;
determine updated location information associated with the one or more mobile devices based on the location invariance measures;
retrain the location model based on a second training dataset that comprises the updated location information to provide a refined location model; and
generate one or more advertisements for at least one mobile device based on location of interest information provided by the refined location model.

2. The system of claim 1 , wherein the one or more storage devices store instructions that are operable, when executed by the one or more computers, to further cause the one or more computers to:
obtain activity information related to the updated location information and associated with the one or more mobile devices, wherein the activity information indicates one or more activities predicted to be conducted by users of the one or more mobile devices.

3. The system of claim 2 , wherein the one or more advertisements is generated based on the location of interest information and the activity information.

4. The system of claim 2 , wherein the one or more storage devices store instructions that are operable, when executed by the one or more computers, to further cause the one or more computers to:
determine, based on the updated location information and the activity information, contextual information comprising one or more relationships between the users of the one or more mobile devices.

5. The system of claim 4 , wherein the one or more advertisements is generated based on the location of interest information and the contextual information.

6. The system of claim 4 , wherein the one or more advertisements is generated based on the location of interest information, the activity information and the contextual information.

7. The system of claim 4 , wherein the one or more storage devices store instructions that are operable, when executed by the one or more computers, to further cause the one or more computers to:
identify activities anticipated to interest a subset of the users of the one or more mobile devices based on the updated location information and the activity information.

8. The system of claim 4 , wherein the one or more mobiles devices comprises a plurality of mobile devices, and wherein the one or more storage devices store instructions that are operable, when executed by the one or more computers, to further cause the one or more computers to:
determine that the plurality of mobile devices are acting together or otherwise engaged in a common activity at a point of interest.

9. The system of claim 2 , wherein the one or more storage devices store instructions that are operable, when executed by the one or more computers, to further cause the one or more computers to:
determine, based on the location of interest information and the activity information, state information regarding movement of the at least one mobile device, wherein the state information indicates a type of transportation method by which the at least one mobile device is moving, and wherein the one or more advertisements is generated based on the location of interest information and the state information.

10. The system of claim 2 , wherein the one or more storage devices store instructions that are operable, when executed by the one or more computers, to further cause the one or more computers to:
determine, based on the location of interest information and the activity information, type information that indicates a duration, purpose, or activity associated with one of the one or more mobile devices, wherein the one or more advertisements is generated based on the location of interest information and the type information.

11. A computer-implemented method, comprising:
training a location model based on a first training dataset that comprises location information associated with a geographic location;
receiving, from one or more global positioning system (GPS) receivers, location information associated with one or more mobile devices in a spatial radius with respect to the geographic location over a period of time;
calculating location invariance measures with respect to the spatial radius over the period of time;
determining updated location information associated with the one or more mobile devices based on the location invariance measures;
retraining the location model based on a second training dataset that comprises the updated location information to provide a refined location model; and
generating one or more advertisements for at least one mobile device based on location of interest information provided by the refined location model.

12. The computer-implemented method of claim 11 , further comprising:
obtaining activity information related to the updated location information and associated with the one or more mobile devices, wherein the activity information indicates one or more activities predicted to be conducted by users of the one or more mobile devices.

13. The computer-implemented method of claim 12 , wherein the generating the one or more advertisements comprises generating the one or more advertisements based on the location of interest information and the activity information.

14. The computer-implemented method of claim 12 , further comprising:
determining, based on the updated location information and the activity information, contextual information comprising one or more relationships between the users of the one or more mobile devices.

15. The computer-implemented method of claim 14 , wherein the generating the one or more advertisements comprises generating the one or more advertisements based on the location of interest information and the contextual information.

16. The computer-implemented method of claim 14 , wherein the generating the one or more advertisements comprises generating the one or more advertisements based on the location of interest information, the activity information and the contextual information.

17. The computer-implemented method of claim 12 , further comprising:
identifying activities anticipated to interest a subset of the users of the one or more mobile devices based on the updated location information and the activity information.

18. A computer program product, stored on a computer readable medium, comprising instructions that when executed by one or more computers cause the one or more computers to:
train a location model based on a first training dataset that comprises location information associated with a geographic location;
receive, from one or more global positioning system (GPS) receivers, location information associated with one or more mobile devices in a spatial radius with respect to the geographic location over a period of time;
calculate location invariance measures with respect to the spatial radius over the period of time;
determine updated location information associated with the one or more mobile device

Assignees

• Groupon Inc

Inventors

• Vengroff Darren E
• Downs Oliver B

Classifications

• G06Q30/02

  Marketing; Price estimation or determination; Fundraising · CPC title

• G06Q30/0205

  based on location or geographical consideration · CPC title

• H04L67/52

  specially adapted for the location of the user terminal · CPC title

• H04W4/02

  Services making use of location information · CPC title

• H04W4/024

  Guidance services · CPC title