Intent-Adaptive GUI Commands for Mobile Display Constraints
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Solution Overview
Problem
Existing graphical user interfaces (GUIs) face challenges in displaying relevant commands based on user intent during a session, leading to user frustration due to buried commands and overpopulation of frequently used options, especially on mobile devices with limited displays.
Innovation Solution
A system that predicts and displays relevant GUI elements by aggregating in-session user activity, filtering out non-relevant intents, and modifying the GUI to show filtered intents, using predictive algorithms to optimize command display based on user product type intent.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If every command is made accessible on the GUI without sub-menus, then command accessibility is improved, but device complexity and display space requirements worsen
Solution Approach 1:
The patent segments commands into frequently used and less frequently used categories, displaying only frequently used commands on the main GUI without sub-menus, while less frequently used commands remain accessible through sub-menus. This segmentation resolves the contradiction by making essential commands immediately accessible while maintaining the structured organization for comprehensive command sets.
Solution Approach 2:
The patent dynamically adjusts the GUI by predicting user intent and modifying the display to show relevant commands based on current user needs. The GUI transitions from a static structure to a dynamic one that adapts to user context, showing only necessary commands at any given moment, thus improving accessibility without permanently increasing complexity.
2Ease of operation
If frequently used commands are displayed on the GUI, then command accessibility is improved, but the GUI becomes overpopulated and pushes out other relevant commands
Solution Approach 1:
The system dynamically predicts user intent and adjusts the GUI display in real-time to show only the subset of frequently used commands that are relevant to the current user context. This prevents overpopulation by adapting the display to show only necessary commands while keeping other relevant commands accessible through alternative means.
Solution Approach 2:
The patent uses predictive algorithms that analyze user behavior patterns and provide feedback to adjust the GUI display. The system learns from user interactions and continuously refines which commands to display, ensuring that frequently used commands are shown without overwhelming the interface, as the display adapts based on actual user needs rather than static frequency data.
3Ease of operation
If predictive algorithms display commands based on historical usage patterns, then frequently used command accessibility is improved, but the approach does not consider user intent for specific usage sessions
Solution Approach 1:
The patent enhances static predictive algorithms by adding dynamic session-specific intent analysis. The system now adapts to user intent within specific usage sessions by analyzing real-time user behavior, contextual information, and current task requirements, allowing the GUI to display commands that are both historically frequent and currently relevant to user needs.
Solution Approach 2:
The system incorporates real-time feedback loops that monitor user interactions during specific sessions and adjust command display accordingly. This feedback mechanism allows the predictive algorithm to consider both historical usage patterns and current session context, refining command recommendations based on actual user intent rather than relying solely on past behavior data.
Data Source
AI summary
Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform: receiving in-session user activity entered into on an initial graphical user interface (GUI) from a user electronic device of a user; pre-processing the in-session user activity to determine one or more intents of the in-session user activity; comparing the one or more intents of the in-session user activity with one or more complementary intents; and coordinating displaying a complimentary GUI on the user device of the user based on the one or more complementary intents. Other embodiments are disclosed herein.