Survey Response Patterning for Accurate Issue and Solution Matching
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Solution Overview
Problem
Existing survey-based prediction algorithms are inaccurate due to their reliance on tree structures and scoring methods, which fail to account for numerous variables, leading to inadequate reflection of individual diversity and ineffective solution recommendations.
Innovation Solution
A method and apparatus that pattern responses to surveys, determine issues based on patterned responses, and propose solution sets using indicator correlations, weights, and AI models to enhance accuracy and relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If tree structure or scoring methods are used for survey-based prediction, then the system is simple and easy to implement, but the prediction accuracy is insufficient because numerous variables cannot be reflected
Solution Approach 1:
The patent replaces traditional mechanical/tree-based prediction structures with an AI-based neural network system. The neural network automatically processes multiple survey variables and patterns without requiring manual tree structure design, thereby improving prediction accuracy while managing complexity through automated learning rather than manual configuration.
Solution Approach 2:
The patent transforms the prediction approach by changing from fixed tree structures to dynamic parameter-based AI modeling. Survey responses are processed as multiple variables that feed into the neural network, allowing the system to adaptively weigh and combine numerous parameters to improve prediction accuracy beyond what fixed tree structures can achieve.
2Adaptability or versatility
If traditional scoring methods are used, then the implementation is straightforward, but individual diversity cannot be adequately reflected leading to ineffective solution recommendations
Solution Approach 1:
The patent replaces mechanical scoring methods with AI-based pattern recognition. The neural network analyzes individual response patterns across multiple survey questions, capturing nuanced individual differences that simple scoring cannot detect. This enables personalized and adaptive solution recommendations tailored to each individual's unique pattern.
Solution Approach 2:
The patent performs preliminary pattern recognition and analysis through the neural network before generating recommendations. By pre-training the AI model on survey data and response patterns, the system is prepared to quickly and accurately identify individual diversity and provide personalized solutions without complex real-time analysis.
Data Source
AI summary
Provided are a method and apparatus for proposing a solution, based on a survey. The method includes storing indicators in a data format in a database, wherein each of the indicators is transformed from a pattern of responses of respondents related to an issue, transforming a response of a user to the survey to a patterned response, the patterned response in the data format, selecting an indicator to be compared with the patterned response among the indicators, the indicators and the patterned response are being in the same data format, determining one or more issues, based on a comparison of the patterned response and the selected indicator, determining a proposal solution set, based on the one or more issues, and displaying the one or more issues and the proposal solution set on a device of the user.