NLP-Based UI Generation for Electronic Device Personalization
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Solution Overview
Problem
Existing display devices require numerous user manipulations to personalize or customize user interface (UI) screens, leading to inconvenience.
Innovation Solution
An electronic device utilizes natural language processing (NLP) to identify user preference information, determine content and visual element information for a UI screen, and generate a personalized UI screen through neural network models, incorporating context and preference data to create a customized interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional manual customization methods are used for UI screens, then users can personalize the interface, but the process requires numerous manipulations and consumes significant time
Solution Approach 1:
The system automatically generates personalized UI screens by analyzing user profile information, preferences, and behavior patterns without requiring manual user manipulation. The electronic device autonomously performs UI customization based on stored user data, eliminating the time-consuming manual configuration process while maintaining high adaptability.
Solution Approach 2:
User preference information and profile data are collected and stored in advance during the user onboarding process. This preliminary data collection enables the system to generate personalized UI screens immediately when needed, without requiring users to spend time on customization at the moment of use.
2Ease of operation
If automated UI generation using NLP and neural networks is implemented, then UI personalization becomes efficient and requires minimal user manipulation, but the device complexity increases
Solution Approach 1:
Natural language processing technology serves as an intermediary that translates user profile information and preferences into structured UI configuration parameters. The NLP module acts as a mediator between the user data storage system and the UI generation system, simplifying the overall architecture by providing a standardized interface for preference interpretation.
Solution Approach 2:
The UI generation process is divided into separate functional modules: user preference analysis, content architecture determination, visual element selection, and UI screen assembly. This segmentation allows each module to be independently optimized and managed, reducing the perceived complexity while enabling sophisticated automated personalization.
Data Source
AI summary
An electronic device, including: at least one processor; and a memory configured to store at least one instruction which, when executed by the at least one processor, causes the electronic device to: identify content preference information associated with a user based on natural language processing (NLP), determine content architecture information corresponding to a user interface (UI) screen and visual element information corresponding to the UI screen based on the content preference information and context information associated with the user, and generate the UI screen based on the content architecture information and the visual element information.