AI Function Mapping for Faster UI Requirement Capture
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Solution Overview
Problem
The traditional UI/UX design and development process is time-consuming due to the need for multiple interviews to capture customer requirements, which are often subject to differing understandings between designers and customers, leading to inefficiencies and prolonged development cycles.
Innovation Solution
A function map generation method and system utilizing an artificial intelligence model to quickly capture customer requirements by executing queries, semantic analysis, and generating a function map based on difficulty points, usage targets, and data sources, reducing the need for iterative interviews.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple interviews are conducted to capture customer requirements, then the accuracy of requirement understanding is improved, but the time cost and development cycle are significantly increased
Solution Approach 1:
The patent applies preliminary action by using an AI model to pre-analyze customer requirements and generate a function map before the actual design process begins. The system performs semantic analysis, function induction, and function association in advance, creating a comprehensive requirement understanding document that guides subsequent design work. This preliminary analysis consolidates what would otherwise require multiple iterative interviews into a single efficient process, capturing accurate requirements while significantly reducing time investment.
2Loss of information
If traditional requirement interview processes are used, then detailed customer needs are captured, but the development efficiency and productivity are reduced
Solution Approach 1:
The patent replaces the mechanical interview process with an AI-based automated system. Instead of relying on human designers to conduct multiple interviews and manually document requirements, the system uses natural language processing, semantic analysis, and machine learning models to automatically extract, analyze, and structure customer requirements. This substitution maintains comprehensive capture of customer needs while dramatically improving development efficiency by eliminating the time-consuming manual interview and documentation process.
3Reliability
If iterative requirement gathering is performed to resolve understanding discrepancies, then the completeness of requirements is improved, but the number of revisions and reconfirmations increases
Solution Approach 1:
The patent implements a feedback mechanism where the AI model continuously refines its understanding of customer requirements through iterative analysis. The system generates a function map, compares it with the original requirements, identifies gaps or inconsistencies, and automatically adjusts its analysis to improve completeness. This automated feedback loop ensures comprehensive requirement capture while reducing process complexity by eliminating the need for manual back-and-forth interviews and reconfirmations between designers and customers.
Data Source
AI summary
A function map generation method and system are provided. The system executes the following steps using an artificial intelligence model. A difficulty point and first data related to the difficulty point are obtained from a first reply content of a first query corresponding to the difficulty point. A usage target and second data related to the usage target are obtained from a second reply content of a second query corresponding to the usage target. An implementation function and a target type are obtained based on the difficulty point and the usage target. A required function is obtained based on the target type. Semantic comparison between the implementation function and the required function is performed to obtain a difference set content. A function map is generated based on the target type, the implementation function, and the difference set content.