Granted Patent B2

US 12,475,422 · App. 18/675,949 · Granted Nov 18, 2025

Inventor: Luis Uva (Miami, FL)

G06Q10/0633G06N3/048

Abstract

Claims (56)

1 . An apparatus for generating a modification target, the apparatus comprising:

at least a processor; and

a memory communicatively connected to the at least a processor, wherein the memory contains instructions configuring the at least a processor to:

prompt a plurality of users related to a process;

receive a plurality of user inputs from the plurality of users as a function of the prompt, wherein the plurality of user inputs comprises information related to sections;

determine a plurality of response modules as a function of the plurality of user inputs, wherein determining the plurality of response modules comprises:

determining a response timing by categorizing the response timing,

wherein categorizing the response timing comprises;

preprocessing training data by at least data cleaning using a data cleaning algorithm;

training a classifier as a function of the preprocessed training data using a classification algorithm to generate a trained classifier; and

categorizing the response timing as a feature of the plurality of user inputs using the trained classifier by identifying a set of data that are clustered together as determined by a threshold of a distance metric;

generate an importance score as a function of the response timing;

generate a modification target as function of the plurality of response modules, the categorization of the response timing and the importance score; and

generate a process enhancement as a function of the modification target using a machine learning model.

2 . The apparatus of claim 1 , wherein the prompt comprises a compound question comprising a set of options for the user to select based on a previous selection.

3 . The apparatus of claim 1 , wherein the memory contains instructions further configuring the at least a processor to prompt the plurality of users as a function of the plurality of user inputs, wherein the plurality of user inputs comprises a rating.

4 . The apparatus of claim 1 , wherein the memory contains instructions further configuring the at least a processor to:

prompt the plurality of users using a chatbot; and

receive the plurality of user inputs using the chatbot.

5 . The apparatus of claim 4 , wherein the plurality of user inputs comprises a textual response from the chatbot, wherein the textual response comprises a survey response.

6 . The apparatus of claim 1 , wherein the memory contains instructions further configuring the at least a processor to determine a priority for the sections of the plurality of user inputs.

7 . The apparatus of claim 6 , wherein the memory contains instructions further configuring the at least a processor to generate the importance score as a function of the priority.

8 . The apparatus of claim 6 , wherein the memory contains instructions further configuring the at least a processor to determine the modification target as a function of the priority.

9 . The apparatus of claim 6 , wherein the memory contains instructions further configuring the at least a processor to:

identify a criteria of a subsection of the sections using the priority, wherein the priority comprises a criteria priority; and

determine the modification target as a function of the criteria.

10 . The apparatus of claim 1 , wherein generating the importance score comprises minimizing an objective function using the response timing.

11 . A method for generating a modification target, the method comprising:

prompting, using at least a processor, a plurality of users related to a process;

receiving, using the at least a processor, a plurality of user inputs from the plurality of users as a function of the prompt, wherein the plurality of user inputs comprises information related to sections;

determining, using the at least a processor, a plurality of response modules as a function of the plurality of user inputs, wherein determining the plurality of response modules comprises:

determining a response timing by categorizing the response timing, wherein categorizing the response timing comprises;

preprocessing training data by at least data cleaning using a data cleaning algorithm;

training a classifier as a function of the preprocessed training data using a classification algorithm to generate a trained classifier; and

categorizing the response timing as a feature of the plurality of user inputs using the trained classifier by identifying a set of data that are clustered together as determined by a threshold of a distance metric;

generating, using the at least a processor, an importance score as a function of the response timing;

generating, using the at least a processor, a modification target as function of the plurality of response modules, the categorization of the response timing and the importance score; and

generating, using the at least a processor, a process enhancement as a function of the modification target using a machine learning model.

12 . The method of claim 11 , wherein the prompt comprises a compound question comprising a set of options for the user to select based on a previous selection.

13 . The method of claim 11 , further comprising:

prompting, using the at least a processor, the plurality of users as a function of the plurality of user inputs, wherein the plurality of user inputs comprises a rating.

14 . The method of claim 11 , further comprising:

prompting, using the at least a processor, the plurality of users using a chatbot; and

receiving, using the at least a processor, the plurality of user inputs using the chatbot.

15 . The method of claim 14 , wherein the plurality of user inputs comprises a textual response from the chatbot, wherein the textual response comprises a survey response.

16 . The method of claim 11 , further comprising:

determining, using the at least a processor, a priority for the sections of the plurality of user inputs.

17 . The method of claim 16 , further comprising:

generating, using the at least a processor, the importance score as a function of the priority.

18 . The method of claim 16 , further comprising:

determining, using the at least a processor, the modification target as a function of the priority.

19 . The method of claim 16 , further comprising:

identifying, using the at least a processor, a criteria of a subsection of the sections using the priority, wherein the priority comprises a criteria priority; and

determining, using the at least a processor, the modification target as a function of the criteria.

20 . The method of claim 11 , further comprising:

minimizing, using the at least a processor, an objective function using the response timing.

Continuity (3)

References Cited (23)