Response Module Ranking for User-Driven Process Modification
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Solution Overview
Problem
Existing systems fail to effectively implement changes based on user feedback, leading to a gap between user input and product/service enhancement.
Innovation Solution
An apparatus and method utilizing a processor and memory to prompt users, receive inputs, determine response modules, categorize response timing, generate importance scores, and create modification targets using machine learning models, enabling automated process enhancements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If user feedback is collected through prompts and responses, then user input is obtained, but the feedback does not lead to actual changes or improvements
Solution Approach 1:
The system implements a closed-loop feedback mechanism where user responses are collected, analyzed through response modules that categorize timing and importance, and then used to generate specific modification targets. This ensures feedback leads to actionable changes rather than being lost
Solution Approach 2:
The system automatically processes user feedback through machine learning models that identify patterns, determine importance scores, and generate modification targets without requiring manual intervention. The system serves itself by converting raw feedback into structured enhancement opportunities
2Measurement precision
If response timing is categorized using a classifier to identify clustered data, then response patterns are understood, but system complexity increases
Solution Approach 1:
The classifier system is divided into multiple response modules that handle different aspects of timing analysis separately. Each module focuses on specific timing patterns, making the overall system more manageable and less complex while maintaining high measurement precision
3Measurement precision
If importance scores are generated based on response timing and multiple response modules, then feedback prioritization is improved, but processing time increases
Solution Approach 1:
Response modules pre-process and categorize timing data as it arrives, preparing structured information before importance scoring begins. This preliminary organization reduces the computational burden during the actual scoring process, maintaining precision while reducing processing time
Data Source
AI summary
An apparatus and method for generating a process enhancement, the apparatus comprising a memory and a processor configured to receive process data, receive user input, determine a plurality of response modules as a function of the user input, determine a modification target as function of the plurality of response modules, wherein determining the modification target includes calculating an importance score for each response module of the plurality of response modules, ranking each response module of the plurality of response modules as a function of the importance score and determining the modification target as a function of the ranking, identify at least a process modification as a function of the process data and the modification target and generate the process enhancement as a function of the at least a process modification.