AI Wireframe Generation from Text Requirements
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Solution Overview
Problem
The existing UI design process is inefficient as it relies heavily on manual wireframe generation, which consumes significant resources and lacks automation in analyzing customer requirements and translating them into well-organized wireframes.
Innovation Solution
A computer-implemented method and system that utilizes two AI models for automated wireframe generation. The first AI model performs named entity recognition (NER) on customer requirements to extract entities and relations, which are then input to a second AI model, such as a generative adversarial network (GAN), to generate a well-organized wireframe that meets customer requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual wireframe generation is used, then designers can create customized wireframes, but the process consumes significant time and resources
Solution Approach 1:
The patent replaces the manual mechanical process of wireframe creation with an automated AI-based system. The first AI model extracts entities and relations from customer requirements, while the second AI model generates the wireframe automatically, eliminating the need for manual dragging and dropping of UI elements.
Solution Approach 2:
The system enables self-service automation where the AI models independently analyze customer requirements and generate wireframes without continuous human intervention. The automated extraction and generation processes allow the system to serve itself in creating wireframes based on input requirements.
2Extent of automation
If manual wireframe generation is used, then designers have full control over the process, but the process lacks automation in analyzing customer requirements
Solution Approach 1:
The patent divides the wireframe generation system into two distinct AI models with specialized functions. The first model handles entity and relation extraction from requirements, while the second model focuses on generating the wireframe structure. This segmentation allows each model to specialize in a specific task, improving overall automation capability.
Solution Approach 2:
The patent introduces an intermediary processing layer between customer requirements and wireframe generation. The first AI model acts as an intermediary that translates unstructured requirements into structured entities and relations, which then serve as input for the second AI model to generate the actual wireframe.
3Ease of operation
If automated AI models are used, then manual effort is reduced, but the system complexity increases
Solution Approach 1:
The patent merges two AI models into a unified wireframe generation system where the outputs of the first model directly feed into the second model. This integration creates a seamless automated process that reduces manual effort while managing system complexity through coordinated operation of the two models.
Data Source
AI summary
A method of this disclosure may include performing a named entity recognition on text information related to requirements for a wireframe by a first artificial intelligence (AI) model, so as to extract entities and relations of the entities from the text information. The method may further comprise inputting the extracted entities and relations to a second AI model to generate the wireframe, wherein the second AI model is trained so that a difference between resultant relations of the entities of the generated wireframe and the extracted relations of the entities from the first AI model is decreased.