IP Library Granted Patent US 12,423,667
Granted Patent B2
US 12,423,667 · App. 18/179,884 · Granted Sep 23, 2025

Systems and methods for the facilitation of blockchains

Inventors: Bjorn Markus Jakobsson (New York, CA); Keir Finlow-Bates (Eura, FI); Stephen C. Gerber (Austin, TX); Guy Stewart (Olympia, WA); Kenneth Rosen (Portola Valley, CA)
Assignee: Artema Labs, Inc
G06Q20/123G06Q20/36H04L67/1097H04L67/306G06Q2220/00
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Quick Facts
Patent No.
US 12,423,667
App. No.
18/179,884
Filed
Mar 7, 2023
Granted
Sep 23, 2025
Kind
B2
Art Unit
3698
USPC
705/67
Abstract

Systems and techniques for enabling the automation of blockchain processes within an NFT platform, through structures and techniques for generating and maintaining descriptors of content and users, are illustrated. One embodiment includes a method for selecting personalized token-directed actions. The method determines a tag including metadata associated with a token. The method determines a profile associated with a user, wherein the user is at least one of an owner of the token and a content creator associated with the token. The method performs a clustering based at least one of the tag and the profile, wherein the clustering includes a collection of tokens sorted according to at least one of shared categories of tokens and shared categories of token users. The method identifies an action corresponding to the token, based on the clustering, wherein the action governs future token access by the user. The method initiates the action.

Claims (56)

1. A method for selecting personalized token-directed actions, comprising:

determining:

a tag associated with a token, wherein the tag:

comprises metadata describing the token; and

corresponds to a weight, indicative of an accuracy of the tag in describing the token; and

an aggregate profile associated with a user, wherein the aggregate profile comprises a set of records representing token items accessed by the user across a plurality of constituent profiles;

performing a clustering based on at least one of the tag or the aggregate profile, wherein the clustering comprises a collection of tokens sorted according to at least one of a first set of one or more shared categories of tokens or a second set of one or more shared categories of token users;

identifying an action corresponding to the token, based on the clustering, wherein the action governs future token access by the user; and

initiating the action.

2. The method of claim 1 , wherein the metadata comprises at least one of a smart contract associated with the token; a consumer-based quality score associated with the token; or a set of one or more user preferences associated with the token.

3. The method of claim 1 , wherein the action concerns access to a recommendation selected from the group consisting of a content recommendation, an advertisement recommendation, and a product placement recommendation.

4. The method of claim 1 , wherein the tag is generated, at least in part, by a generating party corresponding to a token-associated party selected from the group consisting of the user, an entity mining the token, and a third-party appointed by the user.

5. The method of claim 4 , wherein the weight is:

indicative of a trust level reflecting a reputation, of the generating party, for generating accurate tags; and

used in performing the clustering.

6. The method of claim 1 , wherein the aggregate profile comprises data describing at least one of a need of the user, a capability of the user, a reputation of the user in a corresponding community, or a usage statistic associated with the user.

7. The method of claim 1 , wherein the aggregate profile is:

generated, at least in part, by an entity selected from the group comprising a wallet associated with the user; an aggregating entity associated with the user; and an automated component;

stored in at least one of a wallet associated with the user, a public database, an enterprise gateway server, or an encrypted database; and

based on input from at least one of the user or an administrator.

8. The method of claim 1 , wherein:

the first set of one or more shared categories is associated with the tag;

the second set of one or more shared categories is associated with the aggregate profile; and

performing the clustering comprises determining a fit score reflecting a likelihood that a given token user, belonging to the second set of one or more shared categories, would access a given token, belonging to the first set of one or more shared categories.

9. The method of claim 1 , wherein the clustering is performed using an algorithm selected from the group consisting of a machine learning algorithm, an artificial intelligence algorithm, and a maximum likelihood assessment.

10. The method of claim 1 , wherein:

the action transfers the token from a first blockchain to a second blockchain; and

the second blockchain is a level-two (L2) blockchain that is selected based on at least one of an optimization or a cost estimate.

11. A non-transitory computer-readable medium storing instructions that, when executed by a processor, is configured to cause the processor to perform operations for selecting personalized token-directed actions comprising:

determining:

a tag associated with a token, wherein the tag:

comprises metadata describing the token; and

corresponds to a weight, indicative of an accuracy of the tag in describing the token; and

an aggregate profile associated with a user, wherein the aggregate profile comprises a set of records representing token items accessed by the user across a plurality of constituent profiles;

performing a clustering based on at least one of the tag or the aggregate profile, wherein the clustering comprises a collection of tokens sorted according to at least one of a first set of one or more shared categories of tokens or a second set of one or more shared categories of token users;

identifying an action corresponding to the token, based on the clustering, wherein the action governs future token access by the user; and

initiating the action.

12. The non-transitory computer-readable medium of claim 11 , wherein the metadata comprises at least one of a smart contract associated with the token; a consumer-based quality score associated with the token; or a set of one or more user preferences associated with the token.

13. The non-transitory computer-readable medium of claim 11 , wherein the action concerns access to a recommendation selected from the group consisting of a content recommendation, an advertisement recommendation, and a product placement recommendation.

14. The non-transitory computer-readable medium of claim 11 , wherein the tag is generated, at least in part, by a generating party corresponding to a token-associated party selected from the group consisting of the user, an entity mining the token, and a third-party appointed by the user.

15. The non-transitory computer-readable medium of claim 14 , wherein the weight is:

indicative of a trust level reflecting a reputation, of the generating party, for generating accurate tags; and

used in performing the clustering.

16. The non-transitory computer-readable medium of claim 11 , wherein the aggregate profile comprises data describing at least one of a need of the user, a capability of the user, a reputation of the user in a corresponding community, or a usage statistic associated with the user.

17. The non-transitory computer-readable medium of claim 11 , wherein the aggregate profile is:

generated, at least in part, by an entity selected from the group comprising a wallet associated with the user; an aggregating entity associated with the user; and an automated component;

stored in at least one of a wallet associated with the user, a public database, an enterprise gateway server, or an encrypted database; and

based on input from at least one of the user or an administrator.

18. The non-transitory computer-readable medium of claim 11 , wherein:

the first set of one or more shared categories is associated with the tag;

the second set of one or more shared categories is associated with the aggregate profile; and

performing the clustering comprises determining a fit score reflecting a likelihood that a given token user, belonging to the second set of one or more shared categories, would access a given token, belonging to the first set of one or more shared categories.

19. The non-transitory computer-readable medium of claim 11 , wherein the clustering is performed using an algorithm selected from the group consisting of a machine learning algorithm, an artificial intelligence algorithm, and a maximum likelihood assessment.

20. The non-transitory computer-readable medium of claim 11 , wherein:

the action transfers the token from a first blockchain to a second blockchain; and

the second blockchain is a level-two (L2) blockchain that is selected based on at least one of an optimization or a cost estimate.

Assignments (5)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 26, 2024
From: STEWART, GUY
To: ARTEMA LABS, INC
Reel/Frame 069416/0594 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 8, 2024
From: ROSEN, KENNETH
To: ARTEMA LABS, INC
Reel/Frame 068230/0507 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 8, 2024
From: GERBER, STEPHEN C.
To: ARTEMA LABS, INC
Reel/Frame 068230/0628 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 8, 2024
From: JAKOBSSON, BJORN MARKUS
To: ARTEMA LABS, INC
Reel/Frame 068230/0435 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 8, 2024
From: FINLOW-BATES, KEIR
To: ARTEMA LABS, INC
Reel/Frame 068230/0517 →
Continuity (6)
Provisional Application 63477684 · Dec 29, 2022
Provisional Application 63385921 · Dec 2, 2022
Provisional Application 63380739 · Oct 24, 2022
Provisional Application 63365267 · May 24, 2022
Provisional Application 63317348 · Mar 7, 2022
Related Publication 20230281583A1 · Sep 7, 2023
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