Systems and methods for recommending a retail location

• US 8,944,314 B2
• Filed: 11/29/2012
• Issued: 02/03/2015
• Est. Priority Date: 11/29/2012
• Status: Active Grant

• Current Assignee: eBay Inc.
• Original Assignee: eBay Inc.
• Inventors: Lyman, Nate
• Primary Examiner(s): VO, TUYEN KIM
• Application Number:
  US13/689,479
• Publication Number:
  US 20140144979A1
• Time in Patent Office: 796 Days
• Field of Search: 235/375, 235/383, 235/385, 235/462.01, 235/462.45
• US Class Current: 235/375
• CPC Class Codes: G06K 19/06037 multi-dimensional coding
• CPC Class Codes: G06K 7/1417 2D bar codes
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products
• CPC Class Codes: G06Q 30/0629 for generating comparisons
• CPC Class Codes: G06Q 30/0631 Item recommendations
• CPC Class Codes: G06Q 30/0639 Item locations
• CPC Class Codes: H04W 4/023 using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds

Abstract

A method and a system are disclosed for generating a recommendation of a retail location on a network-based system. For example, a system may obtain a retail location definition associated with a geographic location. The geographic location may represent the retail location. The system then builds a scan event model from product scan messages received from a plurality of scanning devices located within the geographic location. The scan event model may include one or more scan events each being associated with a product definition and the retail location definition. Next, a recommendation query from the search device is received by the system. The recommendation query may include a product identifier and a query location. The system may generate a recommendation of the retail location based on determining that the product identifier and the query location match the one or more scan events of the scan event model.

Claims

1. A computer system configured to generate a recommendation of a retail location comprising:

a location tracker module configured to obtain a retail location definition associated with a geographic location representing the retail location;

a scan event handler configured to build a scan event model from historical product scan messages previously received from a plurality of scanning devices associated with a plurality of users located within the geographic location, the scan event model including one or more scan events each being associated with a product definition and the retail location definition, each of the scan events being associated with one of the historical product scan messages previously received from the plurality of scanning devices associated with the plurality of users; and

a recommendation engine comprising at least one processor and configured to;

receive a recommendation query from a search device associated with a specific user, the recommendation query including a product identifier and a query location; and

generate the recommendation of the retail location based on determining that the product identifier and the query location included in the recommendation query match one or more of the scan events of the scan event model that are associated with the historical product scan messages previously received from the plurality of scanning devices associated with the plurality of users.

2. The computer system of claim 1, wherein, in building the scan event model, the scan event handler is further configured to:

receive a first product scan message that includes data derived from a product code attached to a product and a scan location;

determine that the product definition matches the data derived from the product code;

determine that the geographic location associated with the retail location definition matches the scan location; and

update the scan event model to include a scan event associated with the product definition and the retail location definition.

3. The computer system of claim 2, wherein the product code is a universal product code (UPC).

4. The computer system of claim 1, wherein the product scan messages are received responsive to the users associated with the plurality of scanning devices scanning a universal product code (UPC) attached to a product.

5. The computer system of claim 1, further comprising, responsive to receiving one of the product scan messages, the scan event handler is further configured to:

obtain a product identifier from the one of the product scan messages;

match the product identifier with the product definition; and

send data derived from the product definition to a scanning device that previously sent the one of the product scan messages.

6. The computer system of claim 1, wherein, in generating the recommendation of the retail location, the recommendation engine is further configured to select the retail location definition based on a location rule that compares the query location to the geographic location.

7. The computer system of claim 6, wherein, in generating the recommendation of the retail location, the recommendation engine is further configured to select the retail location definition based on a product availability rule that determines that the retail location definition is associated with a scan event that matches the product identifier.

8. The computer system of claim 6, wherein, in generating the recommendation of the retail location, the recommendation engine is further configured to select the retail location definition based on a product availability rule that:

determines that the retail location definition is associated with a number of scan event matching the product identifier, and

selects the retail location definition based on a comparison of the number with a product scan event threshold value.

9. The computer system of claim 6, wherein, in generating the recommendation of the retail location, the recommendation engine is further configured to select the retail location definition based on a product availability rule that:

determines that a number of other retail location definitions are associated with scan events matching the product identifier;

determines that the other retail location definitions and the retail location definition are associated with a merchant definition; and

selects the retail location definition based on a comparison of the number of other retail location definitions with a number of all retail location definitions associated with the merchant definition.

10. The computer system of claim 1, wherein each of the product scan messages requests information regarding a product associated with the product definition.

11. A computer-implemented method of generating a recommendation of a retail location comprising:

obtaining a retail location definition associated with a geographic location representing the retail location;

building a scan event model from historical product scan messages previously received from a plurality of scanning devices associated with a plurality of users located within the geographic location, the scan event model including one or more scan events each being associated with a product definition and the retail location definition, each of the scan events being associated with one of the historical product scan messages previously received from the plurality of scanning devices associated with the plurality of users;

receiving a recommendation query from a search device associated with a specific user, the recommendation query including a product identifier and a query location; and

generating, by a hardware processor, a recommendation of the retail location based on determining that the product identifier and the query location included in the recommendation query match one or more of the scan events of the scan event model that are associated with the historical product scan messages previously received from the plurality of scanning devices associated with the plurality of users.

12. The computer-implemented method of claim 11, wherein building the scan event model further comprises:

receiving a first product scan message that includes data derived from a product code attached to a product and a scan location;

determining that the product definition matches the data derived from the product code;

determining that the geographic location associated with the retail location definition matches the scan location; and

updating the scan event model to include a scan event associated with the product definition and the retail location definition.

13. The computer-implemented method of claim 12, wherein the product code is a universal product code (UPC).

14. The computer-implemented method of claim 11, wherein the product scan messages are received responsive to the users associated with the plurality of scanning devices scanning a universal product code (UPC) attached to a product.

15. The computer-implemented method of claim 11, further comprising, responsive to receiving one of the product scan messages:

obtaining data derived from a product code from the one of the product scan messages;

matching the data derived from the product code with the product definition; and

sending data derived from the product definition to a scanning device that previously sent the one of the product scan messages.

16. The computer-implemented method of claim 11, wherein generating the recommendation of the retail location comprises selecting the retail location definition based on a location rule that compares the query location to the geographic location.

17. The computer-implemented method of claim 16, wherein generating the recommendation of the retail location further comprises further selecting the retail location definition based on a product availability rule that determines that the retail location definition is associated with a scan event that matches the product identifier.

18. The computer-implemented method of claim 16, wherein generating the recommendation of the retail location further comprises further selecting the retail location definition based on a product availability rule that:

determines that the retail location definition is associated with a number of scan event matching the product identifier, and

selects the retail location definition based on a comparison of the number with a product scan event threshold value.

19. The computer-implemented method of claim 16, wherein generating the recommendation of the retail location further comprises further selecting the retail location definition based on a product availability rule that:

determines that a number of other retail location definitions are associated with scan events matching the product identifier;

determines that the other retail location definitions and the retail location definition are associated with a merchant definition; and

selects the retail location definition based on a comparison of the number of other retail location definitions with a number of all retail location definitions associated with the merchant definition.

20. A non-transitory computer-readable medium storing executable instructions thereon, which, when executed by a processor, cause the processor to perform operations that generate a recommendation of a retail location, the operations comprising:

obtaining a retail location definition associated with a geographic location representing the retail location;

building a scan event model from historical product scan messages previously received from a plurality of scanning devices associated with a plurality of users located within the geographic location, the scan event model including one or more scan events each being associated with a product definition and the retail location definition, each of the scan events being associated with one of the historical product scan messages previously received from the plurality of scanning devices associated with the plurality of users;

receiving a recommendation query from a search device associated with a specific user, the recommendation query including a product identifier and a query location; and

generating a recommendation of the retail location based on determining that the product identifier and the query location included in the recommendation query match one or more of the scan events of the scan event model that are associated with the historical product scan messages previously received from the plurality of scanning devices associated with the plurality of users.