Systems and methods to select locations of interest based on distance from route points or route paths

• US 9,736,646 B2
• Filed: 07/13/2016
• Issued: 08/15/2017
• Est. Priority Date: 01/25/2013
• Status: Active Grant

• Current Assignee: Visa International Service Association (Visa, Inc.)
• Original Assignee: Visa International Service Association (Visa, Inc.)
• Inventors: Spears, Joseph, Stan, Patrick, Carlson, Mark
• Primary Examiner(s): Appiah, Charles
• Assistant Examiner(s): HOLLIDAY, JAIME MICHELE
• Application Number:
  US15/208,989
• Publication Number:
  US 20160323711A1
• Time in Patent Office: 398 Days
• Field of Search: 4554141-4142, 4554561-4566
• CPC Class Codes: G01C 21/3484 Personalized, e.g. from learned user behaviour or user-defined profiles
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04W 4/02 Services making use of location information
• CPC Class Codes: H04W 4/022 with dynamic range variability
• CPC Class Codes: H04W 4/023 using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
• CPC Class Codes: H04W 4/024 Guidance services
• CPC Class Codes: H04W 4/026 using orientation information, e.g. compass
• 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 8/18 Processing of user or subscriber data, e.g. subscribed services, user preferences or user profiles; Transfer of user or subscriber data

Abstract

Selection of offers, locations or merchants based on their distances from a portion of a user'"'"'s route and their affinity for the user is disclosed. A route employed by a user for travelling to a destination is obtained and segmented at identified vertices. Locations that are proximate to the route segments are determined. The proximate locations are further analyzed to obtain their specific distances from a selected portion such as the user'"'"'s origin or destination or any route segment. Location based services are associated with those proximate locations that are closest to the selected portion on the user'"'"'s route or those with the better utility.

Claims

1. A computer-implemented method, comprising:

identifying, by a computing apparatus, a plurality of locations;

determining, by the computing apparatus and based on a current location of a user along a route, a portion of the route from which respective distances from the locations are computed;

computing, by the computing apparatus, the respective distances from the locations to the portion of the route of predicted travel of the user;

computing, by the computing apparatus, affinity values of the user for the locations based on electronic payment transaction data of the user;

computing respective utility values of the locations from a predetermined function based on the affinity values of the user for the locations and the respective distances of the locations, wherein each utility value of a location is the predetermined function of an affinity value of the user for the location, and a distance of the location to the route, where the utility value of the location computed from the predetermined function increases when the affinity value of the user for the location increases, and when the distance of the location decreases;

ranking, by the computing apparatus, the locations based on the respective utility values;

selecting, by the computing apparatus, one or more top ranked locations from the plurality of locations based on the utility values; and

presenting, by the computing apparatus to the user, the one or more selected locations.

2. The computer implemented method of claim 1, wherein the utility value of the location is proportional to the affinity value of the user for the location.

3. The computer implemented method of claim 1, wherein the utility value of the location is inverse proportional to the distance of the location to the route.

4. The computer implement method of claim 1, wherein the utility value of the location is proportional to the affinity value of the user for the location divided by the distance of the location to the route.

5. A computing apparatus, comprising:

at least one microprocessor; and

memory storing instructions configured to instruct the at least one microprocessor to at least;

receive, in the computing apparatus, information of routes traversed by a user;

identify, by the computing apparatus, locations on the routes;

organize, by the computing apparatus, the routes as a set of route words in a route dictionary, wherein each route word identifies one of the routes using a sequence of symbols, each of the symbols in the route words uniquely identifies one of the locations, each of the locations is uniquely identified by one of the symbols in the route words;

store, by the computing apparatus, information identifying travels of the user along the routes in association with the route words in the route dictionary, including frequency of travel along routes as term frequency of the route words;

predict, by the computing apparatus using the route dictionary, a remaining portion of a current route of a user from the route dictionary based on looking up in the route dictionary route words starting with one or more symbols representing one or more locations on a traversed portion the current route that have been traversed by the user;

identify, by the computing apparatus, a plurality of points of interest

determine, by the computing apparatus and based on a current location of the user along the current route, a portion of the current route from which distances from the points of interests are computed;

compute, by the computing apparatus, the distances from the points of interests to the portion of the current route;

compute, by the computing apparatus, affinity values of the user for the points of interests base on electronic payment transaction data of the user;

combine, by the computing apparatus, the distances and the affinity values to generate utility values of the points of interests;

select, by the computing apparatus, top points of interests based on the utility values; and

present, by the computing apparatus, the top points of interests to the user while the user is traversing the current route.

6. The computing apparatus of claim 5, wherein the distances from the points of interests are computed to the remaining portion of the current route.

7. The computing apparatus of claim 5, wherein the distances from the points of interests are computed to an origin or destination of the current route.

8. The computing apparatus of claim 5, wherein the distances from the points of interests are computed to respective segments of the route that are closest to the locations respectively.

9. The computing apparatus of claim 5, wherein the utility values for each of the locations is a product of the affinity value and the respective distance of each location from the selected portion.

10. A non-transitory computer storage medium storing instructions configured to instruct a computing apparatus to perform a method, the method comprising:

identifying, by a computing apparatus, a route to be traversed by a user;

identifying, by the computing apparatus, a plurality of points of interest;

determining, by the computing apparatus, lengths of line segments of the route;

computing, by the computing apparatus, threshold lengths for a set of vertexes of the route as combination of the lengths of the line segments of the route and a threshold value;

dividing, by the computing apparatus, the plurality of points of interest into;

a first subset of points of interest within an area around the route, wherein each of the first subset of points of interest has a distance to a vertex among the vertexes of the route less than a respective threshold length associated with the vertex; and

a second subset of points of interest outside an area around the route, wherein each of the second subset of points of interest has distances to the vertexes of the route greater than respective threshold lengths associated with the vertexes;

determining, by the computing apparatus and based on a current location of the user along the route, a portion of the route from which distances from the first subset of points of interests are computed;

computing, by the computing apparatus, the distances from the first subset of points of interests to the portion of the route;

computing, by the computing apparatus, affinity values of the user for the first subset of points of interests base on electronic payment transaction data of the user;

combining, by the computing apparatus, the distances and the affinity values to generate utility values of the first subset of points of interests;

selecting, by the computing apparatus, top points of interests based on the utility values; and

communicating, by the computing apparatus, the top points of interests to the user.

11. The non-transitory computer storage medium of claim 10, wherein the distances from the first subset of points of interests are computed to an origin or destination of the route.

12. The non-transitory computer storage medium of claim 10, wherein the distances from the first subset of points of interests are computed to respective route segments of the route that are closest to the locations respectively.

13. The non-transitory computer storage medium of claim 10, wherein the utility values are proportional to the affinity values and inverse proportional to the distances.

14. The non-transitory computer storage medium of claim 10, wherein the threshold lengths are a predetermined function of:

the lengths of the line segments of the route; and

the threshold value.