Adaptive Display Representation Based on Learned User Behavior
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Electronic devices often display information in static representations that may not be optimal for individual user preferences, leading to suboptimal user interaction and goal satisfaction, as users respond differently to various forms of information representation.
Innovation Solution
An electronic device with a processor and non-transitory computer-readable medium that selects and displays a representation of information based on learned user behavior, monitoring interactions to determine the most effective representation for aligning with user goals without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a static representation of information is displayed on the electronic display, then the device complexity is reduced and ease of operation is improved, but the adaptability to individual user preferences deteriorates
Solution Approach 1:
The system dynamically adjusts the representation of information based on learned user behavior. The electronic display transitions from showing static representations to automatically selecting from multiple representations (numeral, percentage, graph, icon, color) based on real-time analysis of user interactions and preferences, making the display adaptive rather than fixed
Solution Approach 2:
The system performs self-learning by automatically monitoring and analyzing user interactions with the device. The processor continuously learns user preferences for information representation without requiring explicit user input or configuration, and autonomously selects the most appropriate representation format to display
2Adaptability or versatility
If multiple representations of information are made available to match individual user preferences, then adaptability is improved, but device complexity increases
Solution Approach 1:
The system automatically monitors user interactions and learns preferences without requiring user configuration. The processor autonomously analyzes interaction patterns and selects appropriate representations, eliminating the need for manual setup or complex user interface controls for switching representations
Solution Approach 2:
The system changes the representation parameters (format, style, detail level) of displayed information based on learned user preferences. The processor dynamically adjusts which representation type is shown by modifying display parameters rather than requiring separate systems for each representation type
3Adaptability or versatility
If the electronic display automatically adapts to user preferences through learning behavior, then adaptability and user satisfaction are improved, but device complexity and processing requirements increase
Solution Approach 1:
The system performs self-learning by automatically monitoring and analyzing user interactions with the device. The processor continuously learns user preferences for information representation without requiring explicit user input or configuration, and autonomously selects the most appropriate representation format to display
Solution Approach 2:
The system uses feedback from user interactions to continuously improve its selection of information representations. By monitoring user behavior patterns and responses to different representation types, the system refines its understanding of user preferences and adjusts future display choices accordingly
Data Source
AI summary
Electronic devices and methods for displaying information on electronic displays of electronic devices based on learned user behavior are disclosed. In one embodiment, an electronic device includes an electronic display, a processor, and a non-transitory computer-readable medium storing instructions that, when executed by the processor, causes the processor to cause for display on the electronic display a selected representation of information among a plurality of representations based at least in part on learned behavior of a user.