User Interface Content Matching via Style Feature Extraction
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Solution Overview
Problem
Information handling systems face challenges in dynamically managing user interface content to maintain user immersion and relevance, particularly in varying styles and themes across primary and secondary content items.
Innovation Solution
A method and system that identify primary and secondary content features through extraction and comparison, using machine learning to rank and update the user interface with matching content items, and optionally modify secondary content to align with primary content styles, including applying color filters and keyframe selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If secondary content items are automatically selected and displayed in the user interface, then the quantity and variety of content is improved, but the consistency of style and theme deteriorates
Solution Approach 1:
The system extracts style features from the primary content item and applies them as a filter to secondary content items. This ensures that while multiple content items are displayed, each item locally adapts to match the style characteristics of the primary content, thereby maintaining overall style consistency across the interface.
Solution Approach 2:
The system modifies parameters of secondary content items (such as color filters, visual effects, or presentation attributes) based on the style features extracted from the primary content item. By dynamically changing these parameters, the system maintains style consistency while displaying diverse content items.
2Measurement precision
If content feature extraction and comparison is performed for all secondary content items, then the relevance and accuracy of content matching is improved, but the computational complexity and processing time deteriorates
Solution Approach 1:
The system extracts only the essential style features from the primary content item and uses these extracted features as comparison criteria for secondary content items. By taking out and focusing on key style attributes rather than analyzing all content characteristics, the system achieves accurate matching while reducing computational complexity.
3Ease of operation
If the user interface is dynamically updated with matched secondary content items, then the user experience and engagement are improved, but the frequency of updates and system resource consumption deteriorates
Solution Approach 1:
The system performs content feature extraction and matching in advance, before the user actually requests or interacts with the content. By preparing and pre-matching secondary content items based on the primary content's style features, the system can quickly update the interface without requiring frequent real-time processing, thus improving user experience while reducing continuous resource consumption.
Data Source
AI summary
Managing content of a user interface, including identifying an UI application that provides for display a UI on a display device, the UI application providing a primary content item for inclusion by the UI; identifying a request for a secondary content item to be included within the UI, and in response, identifying one or more secondary content items; performing content feature extraction of the primary content item to identify primary content features; performing content feature extraction of the secondary content items to identify secondary content features; comparing the primary content features and the secondary content features to identify similarities therebetween; sorting the secondary content features based on the similarity between the secondary content features and the primary content features; identifying a particular secondary content item of the one or more secondary content items; updating the UI to include the particular secondary content item within the UI.