IP Library Granted Patent US 11,836,781
Granted Patent B2
US 11,836,781 · App. 17/455,058 · Granted Dec 5, 2023

System and method for generating purchase recommendations based on geographic zone information

Inventor: Daniel Langdon (Santiago, CL)
Assignee: Groupon, Inc.
G06Q30/0631G06Q30/0205G06Q30/0243
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Quick Facts
Patent No.
US 11,836,781
App. No.
17/455,058
Granted
Dec 5, 2023
Kind
B2
Abstract

Embodiments provide computer apparatuses, computer systems and computer-executable methods for recommending a commercial item or entity to a consumer based on geographic zone data. The method includes receiving a first predetermined geographic zone, a first importance score associated with a consumer for the first predetermined geographic zone, and a second importance score associated with a commercial item or entity for the first predetermined geographic zone. The method also includes programmatically generating an overlap score based on the first and second importance scores, and programmatically generating a relevancy score based on the overlap score, the relevancy score indicating a probability that the commercial item or entity is of relevance to the consumer. The method further includes, based on the relevancy score, transmitting instructions to a computing device associated with the consumer to cause the computing device to render a representation of the commercial item or entity.

Claims (41)

1. An apparatus for generating training data for a probabilistic technique, the apparatus comprising at least one processor and at least one memory including computer-executable program instructions, the computer-executable program instructions configured to, with the at least one processor, cause the apparatus to at least:

receive, via a network device, an indication of a first geographic zone, a first importance score associated with a consumer for the first geographic zone, and a second importance score associated with a commercial item or entity for the first geographic zone;

programmatically generate an overlap score based on the first and second importance scores;

programmatically generate a relevancy score based on the overlap score, the relevancy score indicating a probability that the commercial item or entity is of relevance to the consumer;

store, on a non-transitory computer-readable medium, the relevancy score in association with identifications of the consumer and the commercial item or entity;

based on the relevancy score, transmit computer-executable instructions via the network device to a computing device associated with the consumer to cause the computing device to render a representation of the commercial item or entity; and

store, on the transitory computer-readable medium as training data, the consumer data, the first importance score, the second importance score, and the relevancy score, wherein the training data is used to train a minimum score for another commercial item or entity.

2. The apparatus of claim 1 , wherein the computer-executable program instructions are further configured to, with the at least one processor, cause the apparatus to at least:

generate, using a random walk technique, the minimum score for the other commercial item or entity.

3. The apparatus of claim 1 , wherein the commercial item is a product, a good, a service, an experience, or a promotion offered by a promotion and marketing service.

4. The apparatus of claim 1 , wherein the first geographic zone encompasses a plurality of geographic locations.

5. The apparatus of claim 1 , wherein the overlap score is generated based on a database join operation.

6. The apparatus of claim 1 , wherein the representation of the commercial item or entity indicates a rank of the commercial item or entity, the rank indicating a relevance of the commercial item or entity to the consumer among a plurality of commercial items or entities.

7. The apparatus of claim 1 , wherein the first importance score is generated based on importance scores for the first geographic zone and the one or more additional geographic zones.

8. A computer-implemented method for generating training data for a probabilistic technique, the computer-implemented method comprising:

receiving, by at least one processor and via a network device, an indication of a first geographic zone, a first importance score associated with a consumer for the first geographic zone, and a second importance score associated with a commercial item or entity for the first geographic zone;

programmatically generating, by the at least one processor, an overlap score based on the first and second importance scores;

programmatically generating, by the at least one processor, a relevancy score based on the overlap score, the relevancy score indicating a probability that the commercial item or entity is of relevance to the consumer;

storing, by the at least one processor and on a non-transitory computer-readable medium, the relevancy score in association with identifications of the consumer and the commercial item or entity;

based on the relevancy score, transmitting, by the at least one processor, computer-executable instructions via the network device to a computing device associated with the consumer to cause the computing device to render a representation of the commercial item or entity; and

storing, on the transitory computer-readable medium as training data, the consumer data, the first importance score, the second importance score, and the relevancy score, wherein the training data is used to train a minimum score for another commercial item or entity.

9. The computer-implemented method of claim 8 , further comprising:

generating, by the at least one processor, using a random walk technique, the minimum score for the other commercial item or entity.

10. The computer-implemented method of claim 8 , wherein the commercial item is a product, a good, a service, an experience, or a promotion offered by a promotion and marketing service.

11. The computer-implemented method of claim 8 , wherein the first geographic zone encompasses a plurality of geographic locations.

12. The computer-implemented method of claim 8 , wherein the overlap score is generated based on a database join operation.

13. The computer-implemented method of claim 8 , wherein the representation of the commercial item or entity indicates a rank of the commercial item or entity, the rank indicating a relevance of the commercial item or entity to the consumer among a plurality of commercial items or entities.

14. The computer-implemented method of claim 8 , wherein the first importance score is generated based on importance scores for the first geographic zone and the one or more additional geographic zones.

15. A computer-program product for generating training data for a probabilistic-technique, the computer program product comprising computer-readable program instructions stored on a non-transitory computer readable medium, the computer-readable program instructions configured, upon execution by a processor, to:

receive, via a network device, an indication of a first geographic zone, a first importance score associated with a consumer for the first geographic zone, and a second importance score associated with a commercial item or entity for the first geographic zone;

programmatically generate an overlap score based on the first and second importance scores;

programmatically generate a relevancy score based on the overlap score, the relevancy score indicating a probability that the commercial item or entity is of relevance to the consumer;

store, on a non-transitory computer-readable medium, the relevancy score in association with identifications of the consumer and the commercial item or entity;

based on the relevancy score, transmit computer-executable instructions via the network device to a computing device associated with the consumer to cause the computing device to render a representation of the commercial item or entity; and

storing, on the transitory computer-readable medium as training data, the consumer data, the first importance score, the second importance score, and the relevancy score, wherein the training data is used to train a minimum score for another commercial item or entity.

16. The computer-program product of claim 15 , wherein the computer-executable program instructions are further configured to, with the at least one processor, cause the apparatus to at least:

generate, using a random walk technique, the minimum score for the other commercial item or entity.

17. The computer-program product of claim 15 , wherein the commercial item is a product, a good, a service, an experience, or a promotion offered by a promotion and marketing service.

18. The computer-program product of claim 15 , wherein the first geographic zone encompasses a plurality of geographic locations.

19. The computer-program product of claim 15 , wherein the overlap score is generated based on a database join operation.

20. The computer-program product of claim 15 , wherein the representation of the commercial item or entity indicates a rank of the commercial item or entity, the rank indicating a relevance of the commercial item or entity to the consumer among a plurality of commercial items or entities.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 12, 2024
From: GROUPON, INC.
To: BYTEDANCE INC.
Reel/Frame 068833/0811 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 12, 2023
From: LANGDON, DANIEL
To: GROUPON, INC.
Reel/Frame 063621/0324 →
Continuity (8)
Continuation 16882846 · May 26, 2020
Continuation 14869536 · Sep 29, 2015
Provisional Application 62057172 · Sep 29, 2014
Provisional Application 62057176 · Sep 29, 2014
Provisional Application 62057157 · Sep 29, 2014
Provisional Application 62057168 · Sep 29, 2014
Provisional Application 62057162 · Sep 29, 2014
Related Publication 20220253916A1 · Aug 11, 2022