IP Library Granted Patent US 12,342,025
Granted Patent B2
US 12,342,025 · App. 18/059,021 · Granted Jun 24, 2025

Systems and methods of dynamic optimization of data element utilization according to objectives

Inventors: Amir Cory (Palo Alto, CA); Shubo Liu (Belmont, CA)
Assignee: ADAP.TV, INC.
H04N21/2668G06F16/23G06F16/25G06F16/285G06F16/70H04N21/23418H04N21/2385H04N21/25883H04N21/812
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Quick Facts
Patent No.
US 12,342,025
App. No.
18/059,021
Granted
Jun 24, 2025
Kind
B2
Abstract

Systems and methods are disclosed for optimizing data element usage according to user-defined objectives, comprising receiving a plurality of user-defined objectives associated with a group of data elements; receiving one or more constraints associated with the group of data elements, wherein at least one of the constraints comprises resources apportionable to each data element in the group of data elements; apportioning at least a portion of the resources to each data element in the group of data elements in a manner that meets the one or more constraints; receiving metrics associated with the performance of the group of data elements in meeting the plurality of user-defined objectives; determining an effectiveness of each data element in the group of data elements for meeting the plurality of user-defined objectives; and automatically revising the at least a portion of resources associated with each data element in the group of data elements.

Claims (67)

1. A computer-implemented method for optimizing graphical data element usage according to a plurality of objectives, comprising:

receiving through a graphical user interface, at a server, a first user input by a user to manually optimize a goal allocation;

receiving through the graphical user interface, at the server, a second user input by the user of a plurality of weighted objectives associated with one or more graphical data elements;

receiving through the graphical user interface, at the server, a third user input by the user of one or more constraints associated with the graphical data elements;

determining, using a recursive optimization algorithm, an optimized allocation of resources based on the weighted objectives and the one or more constraints;

apportioning, by the server, at least a portion of resources to the graphical data elements based on the determined optimized allocation of resources;

automatically displaying, on the graphical user interface, a forecasting graph based on the determined optimized allocation of resources;

receiving through a graphical user interface, at a server, a fourth user input by a user to automatically optimize the goal allocation;

receiving, at the server, one or more distribution performance metrics associated with the performance distribution of the graphical data elements across an electronic network;

determining a minimum level of the one or more distribution performance metrics has been received at the server;

based on the minimum level being reached and the user input to automatically optimize the goal allocation, automatically revising, at the server, the optimized allocation of resources based on the recursive optimization algorithm, the distribution performance metrics, and by selecting a candidate optimization point from one or more candidate optimization points that intersect with points of constraints, the selected candidate optimization point maximizing a highest priority of the plurality of weighted objectives;

distributing, by the server, a remaining portion of fiscal distribution resources associated with each graphical element based on the automatically revised optimized allocation of resources; and

automatically displaying, on the graphical user interface, an adjusted forecasting graph based on the automatically revised optimized allocation of resources.

2. The computer-implemented method of claim 1 , wherein at least one of the fiscal constraints comprises fiscal distribution resources apportionable for the distribution of each graphical data element in the graphical data elements.

3. The computer-implemented method of claim 1 , further comprising:

determining, at the server, an effectiveness of each graphical data element in the graphical data elements for meeting the plurality of weighted objectives, wherein the effectiveness is determined based on the one or more distribution performance metrics.

4. The computer-implemented method of claim 1 , further comprising:

receiving an additional fiscal constraint for association with the one or more fiscal constraints; and

automatically revising the at least a portion of fiscal distribution resources associated with each graphical data element in the graphical data elements based on the additional fiscal constraint.

5. The computer-implemented method of claim 1 , wherein the optimization server comprises a plurality of servers.

6. The computer-implemented method of claim 1 , further comprising:

designating a predetermined minimum allocation of the fiscal distribution resources to each graphical data element in the graphical data elements until a predetermined minimum level of electronic distribution metrics associated with each graphical data element in the graphical data elements is obtained.

7. The computer-implemented method of claim 6 , further comprising:

lowering the predetermined minimum allocation of the fiscal distribution resources for each graphical data element in the graphical data elements as electronic distribution metrics are obtained associated with each graphical data element in the graphical data elements.

8. The computer-implemented method of claim 1 , wherein the one or more distribution performance metrics are determined over a predetermined time interval.

9. The computer-implemented method of claim 1 , wherein each graphical data element in the graphical data elements corresponds to a promotional video.

10. The computer-implemented method of claim 1 , wherein the automatic revising the at least a portion of resources is based on an achievement difficulty.

11. A system for optimizing graphical data element usage according to objectives, the system including:

a data storage device storing instructions for optimizing graphical data element usage according to objectives; and

a processor configured to execute the instructions to perform a method including:

receiving through a graphical user interface, at a server, a first user input by a user to manually optimize a goal allocation;

receiving through the graphical user interface, at the server, a second user input by the user of a plurality of weighted objectives associated with one or more graphical data elements;

receiving through the graphical user interface, at the server, a third user input by the user of one or more constraints associated with the graphical data elements;

determining, using a recursive optimization algorithm, an optimized allocation of resources based on the weighted objectives and the one or more constraints;

apportioning, by the server, at least a portion of resources to the graphical data elements based on the determined optimized allocation of resources;

automatically displaying, on the graphical user interface, a forecasting graph based on the determined optimized allocation of resources;

receiving through a graphical user interface, at a server, a fourth user input by a user to automatically optimize the goal allocation;

receiving, at the server, one or more distribution performance metrics associated with the performance distribution of the graphical data elements across an electronic network;

determining a minimum level of the one or more distribution performance metrics has been received at the server;

based on the minimum level being reached and the user input to automatically optimize the goal allocation, automatically revising, at the server, the optimized allocation of resources based on the recursive optimization algorithm, the distribution performance metrics, and by selecting a candidate optimization point from one or more candidate optimization points that intersect with points of constraints, the selected candidate optimization point maximizing a highest priority of the plurality of weighted objectives;

distributing, by the server, a remaining portion of fiscal distribution resources associated with each graphical element based on the automatically revised optimized allocation of resources; and

automatically displaying, on the graphical user interface, an adjusted forecasting graph based on the automatically revised optimized allocation of resources.

12. The system of claim 11 , wherein the processor is further configured for:

receiving an additional fiscal constraint for association with the one or more fiscal constraints; and

automatically revising the at least a portion of fiscal distribution resources associated with each graphical data element in the graphical data elements based on the additional fiscal constraint.

13. The system of claim 11 , wherein the optimization server comprises a plurality of servers.

14. The system of claim 11 , wherein the processor is further configured for:

designating a predetermined minimum allocation of the fiscal distribution resources to each graphical data element in the graphical data elements until a predetermined minimum level of electronic distribution metrics associated with each graphical data element in the graphical data elements is obtained.

15. The system of claim 14 , wherein the processor is further configured for:

lowering the predetermined minimum allocation of the fiscal distribution resources for each graphical data element in the graphical data elements as electronic distribution metrics are obtained associated with each graphical data element in the graphical data elements.

16. The system of claim 11 , wherein the processor is further configured for automatic revising the at least a portion of resources based on an achievement difficulty.

17. A non-transitory computer-readable medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform a method of optimizing graphical data element usage according to objectives, the method including:

receiving through a graphical user interface, at a server, a first user input by a user to manually optimize a goal allocation;

receiving through the graphical user interface, at the server, a second user input by the user of a plurality of weighted objectives associated with one or more graphical data elements;

receiving through the graphical user interface, at the server, a third user input by the user of one or more constraints associated with the graphical data elements;

determining, using a recursive optimization algorithm, an optimized allocation of resources based on the weighted objectives and the one or more constraints;

apportioning, by the server, at least a portion of resources to the graphical data elements based on the determined optimized allocation of resources;

automatically displaying, on the graphical user interface, a forecasting graph based on the determined optimized allocation of resources;

receiving through a graphical user interface, at a server, a fourth user input by a user to automatically optimize the goal allocation;

receiving, at the server, one or more distribution performance metrics associated with the performance distribution of the graphical data elements across an electronic network;

determining a minimum level of the one or more distribution performance metrics has been received at the server;

based on the minimum level being reached and the user input to automatically optimize the goal allocation, automatically revising, at the server, the optimized allocation of resources based on the recursive optimization algorithm, the distribution performance metrics, and by selecting a candidate optimization point from one or more candidate optimization points that intersect with points of constraints, the selected candidate optimization point maximizing a highest priority of the plurality of weighted objective;

distributing, by the server, a remaining portion of fiscal distribution resources associated with each graphical element based on the automatically revised optimized allocation of resources; and

automatically displaying, on the graphical user interface, an adjusted forecasting graph based on the automatically revised optimized allocation of resources.

18. The non-transitory computer-readable medium of claim 17 , wherein the processor is further configured for:

designating a predetermined minimum allocation of the fiscal distribution resources to each graphical data element in the graphical data elements until a predetermined minimum level of electronic distribution metrics associated with each graphical data element in the graphical data elements is obtained.

19. The non-transitory computer-readable medium of claim 17 , wherein the processor is further configured for automatic revising the at least a portion of resources based on an achievement difficulty.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 1, 2026
From: ADAP.TV LLC
To: YAHOO AGGREGATION HOLDINGS LLC
Reel/Frame 075313/0798 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 1, 2026
From: YAHOO AGGREGATION HOLDINGS LLC
To: YAHOO IP HOLDINGS LLC
Reel/Frame 075314/0306 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 28, 2022
From: CORY, AMIR; LIU, SHUBO
To: ADAP.TV, INC.
Reel/Frame 061890/0184 →