IP Library Granted Patent US 12,321,996
Granted Patent B2
US 12,321,996 · App. 18/297,815 · Granted Jun 3, 2025

Digital search and collaboration process for recommendations, advertising, and buying decisions

Inventors: Tim Costello (Austin, TX); Mark Law (Austin, TX); Krishna Murthy (Austin, TX); Peter Brumme (Austin, TX); Drew Leakey (Austin, TX)
Assignee: Builders Digital Experience, LLC
G06Q50/16G06Q30/0242G06Q30/0276G06Q30/0282G06Q30/0631G06Q30/0643
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Quick Facts
Patent No.
US 12,321,996
App. No.
18/297,815
Granted
Jun 3, 2025
Kind
B2
Abstract

Disclosed are systems, methods, and media having at least one processor; and a non-transitory computer-readable medium storing instruction which, when executed by the at least one processor, cause the at least one processor to perform operations comprising receiving from one or more sources images related to a plurality of features of housing offerings, said images being associated with other images related to features of housing offerings; presenting to a first user an initial prompt and based on response to that initial prompt, presenting a plurality of selectable images related to a first feature of housing offerings; receiving from the first user input regarding the desirability of the images related to the first feature of housing offerings; and iteratively deriving, based on inputs regarding the desirability of the images related to one or more of the plurality of features of housing offerings, a hypothesis regarding a different feature of housing offerings; based at least in part on the hypothesis, presenting to the first user images related to the different feature of housing offerings; and receiving from the first user input regarding the desirability of the images related to the different feature of housing offerings.

Claims (72)

1. A method, comprising:

providing, by a computer system, a plurality of selectable images related to a first feature of product offerings to a first user;

receiving, by the computer system and from a first user input, a user rating preference of images of the plurality of selectable images related to the first feature of product offerings;

iteratively:

deriving, by the computer system and based on inputs regarding the user rating preference of the images related to one or more of a plurality of features of product offerings, a hypothesis regarding a different feature of product offerings using inductive learning techniques, wherein the images are associated with other images related to features of product offerings, and wherein the deriving the hypothesis using the inductive learning techniques includes:

selecting a plurality of hypotheses based on one or more categories, wherein the plurality of hypotheses include at least one of a principal hypothesis or an intermediate hypothesis; and

determining the hypothesis from the plurality of hypotheses when the hypothesis most corresponds with the inputs;

based at least in part on the hypothesis, providing, by the computer system and to the first user, images related to the different feature of product offerings; and

receiving, by the computer system and from the first user, input regarding a user rating preference of the images related to the different feature of product offerings.

2. The method of claim 1 , further comprising:

receiving, from one or more sources, the images related to the plurality of features of product offerings.

3. The method of claim 1 , further comprising:

providing a second plurality of selectable images related to a second feature of product offerings to a second user;

receiving, from the second user, input regarding a second user rating preference of images of the second plurality of selectable images related to the second feature of product offerings;

deriving, based on inputs regarding the second user rating preference of the images related to one or more of the second feature of product offerings, a second hypothesis regarding a second different feature of product offerings;

based at least in part on the second hypothesis, providing, to the second user, images related to the second different feature of product offerings; and

receiving, from the second user, input regarding the second user rating preference of the images related to the different feature of product offerings.

4. The method of claim 3 , further comprising transmitting, to the second user, information representative of the input of the first user.

5. The method of claim 4 , further comprising

presenting, to one or more of the first user and the second user, external information related to a third feature of product offerings;

receiving, from at least one of the first user or the second user, input regarding a user rating preference of the external information related to the third feature of product offerings;

deriving, based on one or more of inputs regarding the external information related to features of product offerings, a third hypothesis regarding a third different feature of product offerings;

based at least in part on the third hypothesis, providing, to at least one of the first user or the second user, external information related to product offerings and images related to the third different feature of product offerings; and

receiving from at least one of the first user or the second user, input regarding a user rating preference of the external information related to product offerings and images related to the third different feature of product offerings.

6. The method of claim 5 , wherein the deriving further comprises deriving, based on inputs from both the first user and the second user regarding the user rating preference of the images related to one or more of the plurality of features of product offerings, a fourth hypothesis regarding a fourth different feature of product offerings.

7. The method of claim 1 , wherein the product offerings include housing offerings.

8. The method of claim 7 , wherein the different feature of housing offerings comprise at least one of a size of a house, a style of the house, a cost of the house, a builder of the house, and a location of the house.

9. A non-transitory computer-readable medium storing instruction which, when executed by at least one processor, cause the at least one processor to perform operations comprising:

providing, by a computer system, a plurality of selectable images related to a first feature of product offerings to a first user;

receiving, by the computer system and from a first user input, a user rating preference of images of the plurality of selectable images related to the first feature of product offerings;

iteratively:

deriving, by the computer system and based on inputs regarding the user rating preference of the images related to one or more of a plurality of features of product offerings, a hypothesis regarding a different feature of product offerings using inductive learning techniques, wherein the images are associated with other images related to features of product offerings, and wherein the deriving the hypothesis using the inductive learning techniques includes:

selecting a plurality of hypotheses based on one or more categories, wherein the plurality of hypotheses include at least one of a principal hypothesis or an intermediate hypothesis; and

determining the hypothesis from the plurality of hypotheses when the hypothesis most corresponds with the inputs;

based at least in part on the hypothesis, providing, by the computer system and to the first user, images related to the different feature of product offerings; and

receiving, by the computer system and from the first user, input regarding a user rating preference of the images related to the different feature of product offerings.

10. The medium of claim 9 , wherein the operations further comprise:

receiving, from one or more sources, the images related to the plurality of features of product offerings.

11. The medium of claim 9 , wherein the operations further comprise:

providing a second plurality of selectable images related to a second feature of product offerings to a second user;

receiving, from the second user, input regarding a second user rating preference of images of the second plurality of selectable images related to the second feature of product offerings;

deriving, based on inputs regarding the second user rating preference of the images related to one or more of the second feature of product offerings, a second hypothesis regarding a second different feature of product offerings;

based at least in part on the second hypothesis, providing, to the second user, images related to the second different feature of product offerings; and

receiving, from the second user, input regarding the second user rating preference of the images related to the different feature of product offerings.

12. The medium of claim 11 , wherein the operations further comprise:

transmitting, to the second user, information representative of the input of the first user.

13. The medium of claim 12 , wherein the operations further comprise:

presenting, to one or more of the first user and the second user, external information related to a third feature of product offerings;

receiving, from at least one of the first user or the second user, input regarding a user rating preference of the external information related to the third feature of product offerings;

deriving, based on one or more of inputs regarding the external information related to features of product offerings, a third hypothesis regarding a third different feature of product offerings;

based at least in part on the third hypothesis, providing, to at least one of the first user or the second user, external information related to product offerings and images related to the third different feature of product offerings; and

receiving from at least one of the first user or the second user, input regarding a user rating preference of the external information related to product offerings and images related to the third different feature of product offerings.

14. The medium of claim 13 , wherein the deriving further comprises deriving, based on inputs from both the first user and the second user regarding the user rating preference of the images related to one or more of the plurality of features of product offerings, a fourth hypothesis regarding a fourth different feature of product offerings.

15. The medium of claim 9 , wherein the product offerings include housing offerings.

16. The medium of claim 15 , wherein the different feature of housing offerings comprise at least one of a size of a house, a style of the house, a cost of the house, a builder of the house, and a location of the house.

17. A system, comprising:

at least one processor; and

a non-transitory computer-readable medium storing instruction which, when executed by the at least one processor, cause the at least one processor to perform operations comprising:

providing a plurality of selectable images related to a first feature of product offerings to a first user;

receiving from a first user input, a user rating preference of images of the plurality of selectable images related to the first feature of product offerings;

iteratively:

deriving, based on inputs regarding the user rating preference of the images related to one or more of a plurality of features of product offerings, a hypothesis regarding a different feature of product offerings using inductive learning techniques, wherein the images are associated with other images related to features of product offerings, and wherein the deriving the hypothesis using the inductive learning techniques includes:

selecting a plurality of hypotheses based on one or more categories, wherein the plurality of hypotheses include at least one of a principal hypothesis or an intermediate hypothesis; and

determining the hypothesis from the plurality of hypotheses when the hypothesis most corresponds with the inputs;

based at least in part on the hypothesis, providing, to the first user, images related to the different feature of product offerings; and

receiving, from the first user, input regarding a user rating preference of the images related to the different feature of product offerings.

18. The system of claim 17 , further wherein the non-transitory computer-readable medium storing instruction which, when executed by the at least one processor, cause the at least one processor to perform operations comprising:

providing a second plurality of selectable images related to a second feature of product offerings to a second user;

receiving, from the second user, input regarding a second user rating preference of images of the second plurality of selectable images related to the second feature of product offerings;

deriving, based on inputs regarding the second user rating preference of the images related to one or more of the second feature of product offerings, a second hypothesis regarding a second different feature of product offerings;

based at least in part on the second hypothesis, providing, to the second user, images related to the second different feature of product offerings; and

receiving, from the second user, input regarding the second user rating preference of the images related to the different feature of product offerings.

Assignments (5)
SECURITY INTEREST Recorded Mar 1, 2024
From: BUILDERS DIGITAL EXPERIENCE, LLC; BUILDER HOMESITE, INC.; MEYERS RESEARCH, LLC
To: BARINGS FINANCE LLC, ADMINISTRATIVE AGENT
Reel/Frame 066619/0714 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 8, 2023
From: COSTELLO, TIMOTHY A.
To: BUILDERS DIGITAL EXPERIENCE, LLC
Reel/Frame 065501/0226 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 8, 2023
From: LAW, MARK; BRUMME, PETER; LEAKEY, DREW
To: BUILDER HOMESITE, INC.
Reel/Frame 065523/0917 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 8, 2023
From: BUILDER HOMESITE, INC.
To: BUILDERS DIGITAL EXPERIENCE, LLC
Reel/Frame 065523/0949 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 10, 2023
From: MURTHY, KRISHNA
To: BUILDERS DIGITAL EXPERIENCE, LLC
Reel/Frame 063273/0284 →
Continuity (3)
Continuation 16436005 · Jun 10, 2019
Provisional Application 62682335 · Jun 8, 2018
Related Publication 20230245253A1 · Aug 3, 2023
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