System And Method For Generating Recommendations Based On Similarities Between Location Information Of Multiple Users

• US 20100280920A1
• Filed: 04/29/2009
• Published: 11/04/2010
• Est. Priority Date: 04/29/2009
• Status: Active Grant

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: Scott, Sean M., Kane, Francis J. JR.
• Granted Patent: US 10,042,032 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G01S 5/0027 of actual mobile position, i.e. position determined on mobile
• CPC Class Codes: G01S 5/0269 Inferred or constrained positioning, e.g. employing knowledge of the physical or electromagnetic environment, state of motion or other contextual information to infer or constrain a position
• CPC Class Codes: G06Q 30/00 Commerce
• CPC Class Codes: G06Q 30/0603 Catalogue ordering
• CPC Class Codes: G06Q 30/0631 Item recommendations

Abstract

Various embodiments of a system and method for generating recommendations based on similarities between location information of multiple users are described. Various embodiments may include a location-based recommendation system configured to, for each given user of a group of users, determine the given user has traveled to one or more respective locations and determine one or more characteristics of the given user. The system may also determine that a particular user has traveled to or will travel to each of one or more particular locations. The system may further determine a similarity between the one or more particular locations and one or more locations to which specific ones of the group of users have traveled. The system may generate a recommendation for the particular user based on at least some of the determined characteristics of the specific ones of the group of users for which the similarity was determined.

Claims

1. A computer-implemented method, comprising:

for each given user of a plurality of users;

receiving user location information for the given user from one or more computing devices associated with the given user, and determining one or more user characteristics for the given user;

receiving user location information for a particular user from one or more computing devices associated with that particular user;

determining a particular subset of the plurality of users that are similar to the particular user, wherein determining the particular subset includes determining a similarity between the user location information of the particular user and the user location information of the particular subset of the plurality of users; and

for said particular user, generating a recommendation based on the user characteristics corresponding to the particular subset of the plurality of users.

2. The computer-implemented method of claim 1, wherein the method further comprises determining one or more user characteristics for the particular user;

wherein determining the particular subset of users further comprises determining a similarity between the user characteristics of the particular user and the user characteristics corresponding to the particular subset of the plurality of users.

3. The computer-implemented method of claim 1, further comprising generating a message comprising the recommendation and sending said message to at least one computing device controlled by the particular user.

4. The computer-implemented method of claim 3, wherein said at least one computing device comprises one or more of:

a mobile telephone, a personal digital assistant, a laptop computer system, a desktop computer system, and a navigation device.

5. The computer-implemented method of claim 1, wherein the user location information for a given user specifies one or more of:

a location to which that user has traveled, a location in which that user is currently traveling, a location to which that user is expected to travel, and a location to which that user is predicted to travel.

6. The computer-implemented method of claim 1, wherein at least some of for the user location information for the plurality of users and the particular user includes information generated based on one or more of:

the global positioning system (GPS), communication tower triangulation, and user-input specifying a location.

7. The computer-implemented method of claim 1, wherein said one or more user characteristics of the given user indicate one or more of:

an item or service purchased by the given user, and a network-based activity performed by the given user.

8. The computer-implemented method of claim 7, wherein said network-based activity includes one or more of:

accessing an item detail page of an e-commerce website, purchasing an item on an e-commerce website, and adding an item to a wish list of items on an e-commerce website.

9. The computer-implemented method of claim 1, wherein said one or more characteristics of the given user comprise an indication that the given user has traveled to a particular place of commerce.

10. The computer-implemented method of claim 1, wherein said recommendation includes one or more of:

a recommended item or service purchased by the particular subset of the plurality of users according to the user characteristics for the particular subset, and a recommended location determined from the user location information for the particular subset.

11. A computer-implemented method, comprising:

for each given location of a plurality of locations;

determining behavior information for a plurality of users that have or are expected to visit that location, wherein at least some of said behavior information is received from one or more computing devices associated with the plurality of users;

for a particular user, receiving user location information indicating a particular location of said plurality of locations from a computing device associated with that user; and

generating a recommendation for the particular user, said recommendation specifying a recommended action based on a statistical analysis of the behavior information for the particular location.

12. The computer-implemented method of claim 11, wherein the recommended action of said recommendation indicates one or more of:

an item to purchase, a service to purchase and a location to visit.

13. The computer-implemented method of claim 11, wherein the user location information for the particular user specifies one or more of:

a location to which that user has traveled, a location in which that user is currently traveling, a location to which that user is expected to travel, and a location to which that user is predicted to travel.

14. The computer-implemented method of claim 11, wherein for a given one of the plurality of users, the behavior information of that user indicates one or more of:

a location to which that user has traveled, a location in which that user is currently traveling, a location to which that user is expected to travel, and a location to which that user is predicted to travel, an item or service purchased by that user, and a network-based activity performed by that user.

15. The computer-implemented method of claim 11, wherein said statistical analysis of the behavior information for the particular location comprises determining the recommended action as being a most popular action performed by the plurality of users in association with that particular location.

16. A system, comprising:

a memory; and

one or more processors coupled to the memory, wherein the memory comprises program instructions to;

for each given user of a plurality of users;

receive user location information for the given user from one or more computing devices associated with the given user, and determine one or more user characteristics for the given user;

receive user location information for a particular user from one or more computing devices associated with that particular user;

determine a particular subset of the plurality of users that are similar to the particular user, wherein that determination comprises determining a similarity between the user location information of the particular user and the user location information of the particular subset of the plurality of users; and

for said particular user, generate a recommendation based on the user characteristics corresponding to the particular subset of the plurality of users.

17. The system of claim 16, wherein the program instructions are configured to determine one or more user characteristics for the particular user;

wherein to determine the particular subset of users, the program instructions are further configured to determine a similarity between the user characteristics of the particular user and the user characteristics corresponding to the particular subset of the plurality of users.

18. The system of claim 16, wherein the program instructions are configured to generate a message comprising the recommendation and send said message to at least one computing device controlled by the particular user.

19. The system of claim 18, wherein said at least one computing device comprises one or more of:

a mobile telephone, a personal digital assistant, a laptop computer system, a desktop computer system, and a navigation device.

20. The system of claim 16, wherein the user location information for a given user specifies one or more of:

a location to which that user has traveled, a location in which that user is currently traveling, a location to which that user is expected to travel, and a location to which that user is predicted to travel.

21. The system of claim 16, wherein at least some of for the user location information for the plurality of users and the particular user includes information generated based on one or more of:

the global positioning system (GPS), communication tower triangulation, and user-input specifying a location.

22. The system of claim 16, wherein said one or more user characteristics of the given user indicate one or more of:

an item or service purchased by the given user, and a network-based activity performed by the given user.

23. The system of claim 22, wherein said network-based activity includes one or more of:

accessing an item detail page of an e-commerce website, purchasing an item on an e-commerce website, and adding an item to a wish list of items on an e-commerce website.

24. The system of claim 16, wherein said one or more characteristics of the given user comprise an indication that the given user has traveled to a particular place of commerce.

25. The system of claim 16, wherein said recommendation includes one or more of:

a recommended item or service purchased by the particular subset of the plurality of users according to the user characteristics for the particular subset, and a recommended location determined from the user location information for the particular subset.

26. A computer-readable storage medium, storing program instructions computer-executable to:

for each given user of a plurality of users;

receive user location information for the given user from one or more computing devices associated with the given user, and determine one or more user characteristics for the given user;

receive user location information for a particular user from one or more computing devices associated with that particular user;

determine a particular subset of the plurality of users that are similar to the particular user, wherein that determination comprises determining a similarity between the user location information of the particular user and the user location information of the particular subset of the plurality of users; and

for said particular user, generate a recommendation based on the user characteristics corresponding to the particular subset of the plurality of users.

27. The system of claim 26, wherein the program instructions are configured to determine one or more user characteristics for the particular user;

wherein to determine the particular subset of users, the program instructions are further configured to determine a similarity between the user characteristics of the particular user and the user characteristics corresponding to the particular subset of the plurality of users.

28. The system of claim 26, wherein the program instructions are configured to generate a message comprising the recommendation and send said message to at least one computing device controlled by the particular user.

29. The system of claim 28, wherein said at least one computing device comprises one or more of:

a mobile telephone, a personal digital assistant, a laptop computer system, a desktop computer system, and a navigation device.

30. The system of claim 26, wherein the user location information for a given user specifies one or more of:

a location to which that user has traveled, a location in which that user is currently traveling, a location to which that user is expected to travel, and a location to which that user is predicted to travel.

31. The system of claim 26, wherein at least some of for the user location information for the plurality of users and the particular user includes information generated based on one or more of:

the global positioning system (GPS), communication tower triangulation, and user-input specifying a location.

32. The system of claim 26, wherein said one or more user characteristics of the given user indicate one or more of:

an item or service purchased by the given user, and a network-based activity performed by the given user.

33. The system of claim 32, wherein said network-based activity includes one or more of:

accessing an item detail page of an e-commerce website, purchasing an item on an e-commerce website, and adding an item to a wish list of items on an e-commerce website.

34. The system of claim 26, wherein said one or more characteristics of the given user comprise an indication that the given user has traveled to a particular place of commerce.

35. The system of claim 26, wherein said recommendation includes one or more of:

a recommended item or service purchased by the particular subset of the plurality of users according to the user characteristics for the particular subset, and a recommended location determined from the user location information for the particular subset.