Vehicle recommendations weighted by user-valued features

• US 10,733,656 B1
• Filed: 03/13/2019
• Issued: 08/04/2020
• Est. Priority Date: 03/13/2019
• Status: Active Grant

• Current Assignee: Capital One Services LLC (Capital One Financial Corporation)
• Original Assignee: Capital One Services LLC (Capital One Financial Corporation)
• Inventors: Price, Micah, Tang, Qiaochu, Hoover, Jason, Ghamsari, Avid, Dagley, Geoffrey
• Primary Examiner(s): Airapetian, Mila
• Application Number:
  US16/352,315
• Time in Patent Office: 510 Days
• Field of Search: None
• CPC Class Codes: G06Q 30/0627 using item specifications
• CPC Class Codes: G06Q 30/0629 for generating comparisons
• CPC Class Codes: G06Q 30/0631 Item recommendations

Abstract

Computer-implemented methods, computer systems, and computer readable media for determining, sorting, or determining and sorting a set of items. The method includes receiving, via a user device, parameter values from a user and receiving parameter weights. The method further includes determining a sort score for each vehicle of a set of vehicles based on the received parameter values and parameter weights, and sorting the set of vehicles based on the sort score of each vehicle of the set of vehicles.

Claims

1. A computer implemented method for determining purchase recommendations, the method comprising:

receiving, via a user device, parameter values from a user;

receiving, via the user device, parameter weights;

generating one or more parameter similarity values for each vehicle of a set of vehicles based on the received parameter values;

determining a sort score for each vehicle of the set of vehicles based on the received parameter weights and generated parameter similarity values; and

sorting the set of vehicles based on the sort score of each vehicle of the set of vehicles.

2. The method of claim 1, further including applying a hard filter to a domain of vehicles to determine the set of vehicles.

3. The method of claim 1, further including determining a subset of vehicles from the set of vehicles based on the sort score of each vehicle.

4. The method of claim 1, further including outputting the sorted set of vehicles to the user device.

5. The method of claim 1, wherein each parameter similarity value is greater than or equal to 0 and less than or equal to 1.

6. The method of claim 1, wherein the one or more parameter similarity values is based on a similarity matrix.

7. The method of claim 1, wherein the sort score for each vehicle of the set of vehicles is determined according to at least one of:

8. The method of claim 1, wherein the one or more parameter values are indicative of a mileage, a fuel economy, a price, one or more luxury features, a drivetrain, a color of a vehicle, accident history, repair history, current aesthetic or mechanical defects, and/or ownership history of a vehicle.

9. The method of claim 1, further comprising transmitting information regarding one or more vehicles of the set of vehicles to the user, a dealer, or another party.

10. A computer implemented method for determining purchase recommendations, the method comprising:

receiving, via a user device, parameter values from a user;

receiving, via the user device, parameter weights;

generating one or more parameter similarity values for each vehicle of a set of vehicles based on the received parameter values;

determining a sort score for each vehicle of the set of vehicles based on the received parameter weights and generated parameter similarity values;

sorting the set of vehicles based on the sort score of each vehicle of the set of vehicles;

outputting the sorted set of vehicles to the user device; and

transmitting information regarding one or more vehicles of the set of vehicles to a dealer or another party;

wherein the sort score for each vehicle of the set of vehicles is determined according to at least one of;

11. The method of claim 10, further including applying a hard filter to a domain of vehicles to determine the set of vehicles.

12. The method of claim 10, further including determining a subset of vehicles from the set of vehicles based on the sort score of each vehicle.

13. The method of claim 10, wherein each parameter similarity value is greater than or equal to 0 and less than or equal to 1.

14. The method of claim 10, wherein the one or more parameter similarity values is based on a similarity matrix.

15. The method of claim 10, wherein the one or more parameter values are indicative of a mileage, a fuel economy, a price, one or more luxury features, a drivetrain, a color of a vehicle, accident history, repair history, current aesthetic or mechanical defects, and/or ownership history of a vehicle.