Apparatus and a method for the generation of exploitation data

Patent metadata

Field	Value
Publication number	US-12499133-B2
Application number	US-202418821146-A
Country	US
Kind code	B2
Filing date	Aug 30, 2024
Priority date	Jan 10, 2024
Publication date	Dec 16, 2025
Grant date	Dec 16, 2025

Abstract

An apparatus for the generation of exploitation data is disclosed. The apparatus comprises at least a processor and a memory communicatively connected to the at least a processor. The memory instructs the processor to receive a plurality of entity profiles from a plurality of entities, wherein each of the plurality of entity profiles comprises a plurality of operational data. The memory instructs the processor to identify demand data as a function of the plurality of entity profiles. The memory instructs the processor to generate exploitation data as a function of the operational data and the demand data. The memory instructs the processor to determine collaboration data as a function of the exploitation data. The memory instructs the processor to display the collaboration data using a display device.

First claim

What is claimed is:

1 . An apparatus for a generation of exploitation data, wherein the apparatus comprises:
at least a processor; and a memory communicatively connected to the at least a processor, wherein the memory containing instructions configuring the at least a processor to:
receive a plurality of entity profiles identifying demand data from a plurality of entities, wherein each of the plurality of entity profiles comprises a plurality of operational data, wherein the plurality of entity profiles additionally comprises a first entity profile and a second entity profile;
identify free zone data as a function of the plurality of entity profiles;
generate exploitation data using an exploitation machine-learning model by:
training the exploitation machine-learning model using exploitation training data, wherein the exploitation training data contains a plurality of data entries containing operational data inputs correlated to exploitation data outputs; and
generating the exploitation data as a function of the operational data and the demand data using a trained exploitation machine-learning model;

determine collaboration data as a function of the free zone data, wherein determining the collaboration data comprises:
classifying the plurality of operational data and the free zone data into a plurality of collaboration categories;
determining an exploitation rank as a function of the exploitation data and the classification of the plurality of operational data into the plurality of collaboration categories;
plotting a plurality of graphical data as a function of the exploitation rank, wherein the plurality of graphical data comprises: a first graphical datum associated with the first entity profile; and a second graphical datum associated with the second entity profile;
determining the collaboration data as a function of a comparison of the first graphical datum and the second graphical datum; and

display the collaboration data using a display device.

2 . The apparatus of claim 1 , wherein the demand data identifies a demand scope.

3 . The apparatus of claim 2 , wherein free zone data comprises an identification of a target business opportunity.

4 . The apparatus of claim 1 , wherein identifying the demand data comprises identifying demand data using a web crawler.

5 . The apparatus of claim 1 , wherein determining the collaboration data comprises a comparison of the first graphical datum and the second graphical datum using a fuzzy inference set.

6 . The apparatus of claim 1 , wherein the memory further instructs the processor to identify a plurality of operational capabilities as a function of the plurality of operational data.

7 . The apparatus of claim 1 , wherein the memory further instructs the processor to generate an attribute quantifier as a function of the plurality of collaboration categories, wherein the attribute quantifier is configured to assign an importance value to each collaboration category of the plurality of collaboration categories.

8 . The apparatus of claim 1 , wherein plotting the plurality graphical data comprises plotting the exploitation rank along a continuum.

9 . A method for a generation of exploitation data, wherein the method comprises: receiving, using at least a processor, a plurality of entity profiles identifying demand data
from a plurality of entities, wherein each of the plurality of entity profiles comprises a plurality of operational data, wherein the plurality of entity profiles additionally comprises a first entity profile and a second entity profile;
identifying, using the at least a processor, free zone data as a function of the plurality of entity profiles;
generating, using the at least a processor, exploitation data using an exploitation machine-learning model by:
training the exploitation machine-learning model using exploitation training data, wherein the exploitation training data contains a plurality of data entries containing operational data inputs correlated to exploitation data outputs; and
generating the exploitation data as a function of the operational data and the demand data using a trained exploitation machine-learning model;

determining, using the at least a processor, collaboration data as a function of the free zone data, wherein determining the collaboration data comprises:
classifying the plurality of operational data into a plurality of collaboration categories;
determining an exploitation rank as a function of the exploitation data and the classification of the plurality of operational data into the plurality of collaboration categories;
plotting a plurality of graphical data as a function of the exploitation rank, wherein the plurality of graphical data comprises:
a second graphical datum associated with the second entity profile; a first graphical datum associated with the first entity profile; and

determining the collaboration data as a function of a comparison of the first graphical datum and the second graphical datum; and
displaying the collaboration data using a display device.

10 . The method of claim 9 , wherein the demand data comprises a demand scope.

11 . The method of claim 10 , wherein free zone data contains an identification of a target business opportunity.

12 . The method of claim 9 , wherein the method further comprises identifying, using the at least a processor, the demand data using a web crawler.

13 . The method of claim 9 , wherein the method further comprises determining, using the at least a processor, the collaboration data comprises a comparison of the first graphical datum and the second graphical datum using a fuzzy inference set.

14 . The method of claim 9 , wherein the method further comprises identifying, using the at least a processor, a plurality of operational capabilities as a function of the plurality of operational data.

15 . The method of claim 9 , wherein the method further comprises generating, using the at least a processor, an attribute quantifier as a function of the plurality of collaboration categories, wherein the attribute quantifier is configured to an importance value to each collaboration category of the plurality of collaboration categories.

16 . The method of claim 9 , wherein plotting the plurality graphical data comprises plotting the exploitation rank along a continuum.

Assignees

• The Strategic Coach Inc

Inventors

• Smith Barbara Sue
• Sullivan Daniel J

Classifications

• G06F16/906

  Clustering; Classification · CPC title

• G06F16/90332 Primary

  Natural language query formulation or dialogue systems · CPC title

• G06F16/951

  Indexing; Web crawling techniques · CPC title

• G06F16/287 Primary

  Visualization; Browsing · CPC title