Split Screen App Matching via AI Feature Extraction
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Solution Overview
Problem
The existing split screen application matching methods on terminals fail to effectively recommend relevant applications, as the application list does not change based on the currently open application, leading to poor user experience.
Innovation Solution
A split screen application matching method using an artificial intelligence model that includes a feature extraction model and a deep learning model to determine a candidate application list based on feature information associated with the first application, ensuring that displayed candidate applications are likely to be the ones the user wants to use.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a static application list is provided for split screen selection, then the system complexity is reduced and ease of operation is improved, but the recommendation effectiveness deteriorates because the list does not change based on the currently open application
Solution Approach 1:
The application list is transformed from a static structure to a dynamic one that automatically updates based on the currently open application. The system dynamically generates different application lists depending on which application is active, making the interface adaptive to the user's current context while maintaining ease of operation through automatic updates without requiring manual intervention.
Solution Approach 2:
The system implements feedback by monitoring which application is currently open and using this information to automatically update the application list for split screen selection. This closed-loop feedback mechanism ensures that the recommended applications are always relevant to the user's current activity, improving recommendation effectiveness while keeping the interaction simple.
2Adaptability or versatility
If the application list changes dynamically based on the currently open application, then the recommendation effectiveness is improved, but the system complexity increases due to the need for real-time detection and updates
Solution Approach 1:
The system performs self-service by automatically detecting the currently open application and updating the application list without requiring user intervention or complex external control mechanisms. The terminal device itself manages the dynamic updates, reducing the need for additional complex systems while achieving effective real-time adaptation.
Solution Approach 2:
The functionality for detecting the current application and generating the updated application list is merged into the existing split screen management system. By combining these functions within the same system module, the patent avoids the complexity that would arise from adding separate independent systems, achieving dynamic adaptation through integrated design.
3Ease of operation
If a generic application list is provided for all applications, then the ease of operation is maintained, but the relevance of recommended applications deteriorates leading to poor user experience
Solution Approach 1:
Instead of providing a uniform application list for all applications, the system applies local quality by customizing the application list according to the specific currently open application. Each application context receives a tailored list of relevant applications, ensuring that the information presented is locally optimized for relevance while maintaining the same ease of operation through consistent interface design.
Data Source
AI summary
A split screen application matching method, including acquiring feature information associated with a first application, based on receiving a split screen instruction; determining a candidate application list using an artificial intelligence model based on the feature information, wherein the artificial intelligence model comprises a feature extraction model and a deep learning model, and the candidate application list comprises at least one candidate second application; and displaying the first application in a first split screen area of the terminal, and displaying the candidate application list in a second split screen area of the terminal.