Adaptive GUI Navigation via Path Frequency Tracking
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Solution Overview
Problem
Existing user interface navigation systems lack the ability to automatically detect and adapt to the most common user actions across different GUI states, leading to inefficiencies and errors due to the need for manual macro definition and lack of adaptivity to changing desktop environments.
Innovation Solution
A system and method that uses a graph representation of the user interface to track and store frequently traversed paths, automatically adding states to a path sequence, measuring elapsed time, and comparing it to a threshold to determine the significance of new paths, which are then stored and presented as direct links for user access, allowing for adaptive and efficient navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If manual macro definition is used, then automation capability is provided, but device complexity and ease of operation deteriorate due to explicit entry requirements
Solution Approach 1:
The system automatically detects user navigation patterns and generates macro definitions without requiring users to manually define or configure them. The monitor autonomously observes GUI state transitions, identifies frequently traversed paths, and creates automated navigation shortcuts based on observed behavior, eliminating the need for explicit user intervention in macro creation.
Solution Approach 2:
The system performs preliminary analysis of user navigation patterns by monitoring and recording GUI state transitions before generating macro definitions. This preliminary observation phase allows the system to pre-identify common navigation paths and prepare automated shortcuts in advance, so they are ready for immediate use without requiring users to manually set them up.
2Extent of automation
If fixed macro sequences are defined, then automation is achieved, but adaptability worsens when desktop environment changes
Solution Approach 1:
The system dynamically adapts macro definitions to changing desktop environments by continuously monitoring current GUI states during macro execution. When environmental changes are detected (such as moved icons or changed window positions), the system adjusts the navigation paths and parameters in real-time, allowing macros to remain effective despite changes in the workspace layout.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor the actual state of the GUI during macro execution and compare it against expected states. When deviations are detected due to environment changes, the system uses this feedback to automatically adjust subsequent navigation actions, ensuring the macro sequence remains valid and achieves the intended result.
3Productivity
If comprehensive path tracking is implemented, then navigation efficiency improves, but loss of time increases due to monitoring overhead
Solution Approach 1:
The system implements partial monitoring by focusing only on the most frequently traversed navigation paths rather than tracking all possible GUI transitions. By identifying and monitoring only the critical paths that constitute the majority of user interactions, the system achieves significant navigation efficiency improvements while minimizing the time overhead associated with comprehensive monitoring.
Data Source
AI summary
A method for automatic advancement of navigation through GUI, involving: (a) providing a graph representing GUI, comprising at least two states and at least one path allowing navigation from one of said states to a different one of said states; (b) clearing a current path; (c) receiving a request to navigate to a state of said states and outputting a suitable response; (d) adding the current state to the current path; (e) starting a timer; (f) receiving a request to navigate to another state of said states and outputting a suitable response; (g) stopping said timer and comparing its result with a threshold value wherein if said result is lower than said threshold, adding information on said another state to the current path; (h) storing the current path in a paths database; and (i) repeating steps (e)-(h) until said result is greater than said threshold.