Automated Interface Region Prioritization via User Interaction Metrics
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Solution Overview
Problem
Automated software tools face challenges in prioritizing interactions with computer software applications and determining whether areas of an application have been previously evaluated, as existing methods require manual intervention and struggle with dynamic changes in hyperlinks.
Innovation Solution
A method is introduced to identify regions of a software application interface with user interaction measures, determining if they meet a predefined minimum level of interaction, and performing automated interactions or comparisons based on these measures, with weighted similarity calculations to assess interface similarity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated tools interact with all interface elements equally, then comprehensive coverage is achieved, but efficiency decreases and manual intervention is required
Solution Approach 1:
The patent applies local quality by assigning different interaction priorities to different regions of the interface based on their user interaction metrics. High-usage regions receive higher prioritization scores, while low-usage regions receive lower scores, allowing the automated tool to focus its efforts where they are most needed rather than treating all regions equally.
Solution Approach 2:
The patent changes the parameter of interaction priority from a uniform value to a dynamic value based on user interaction measurements. By measuring actual user behavior and converting it into prioritization scores, the system adapts its interaction strategy to match real usage patterns, improving automation efficiency.
2Reliability
If all regions are evaluated thoroughly, then evaluation completeness is achieved, but time consumption increases
Solution Approach 1:
The patent applies partial action by evaluating only the most important regions first, based on their user interaction metrics. Rather than evaluating all regions equally, the system focuses on high-usage regions that contribute most to evaluation completeness, accepting that some low-usage regions may be evaluated later or skipped entirely.
Solution Approach 2:
The patent performs preliminary measurement of user interaction metrics before the actual evaluation process. This preliminary action provides the prioritization information needed to guide the subsequent evaluation, allowing the system to avoid time-consuming evaluation of low-priority regions while ensuring high-priority regions are thoroughly assessed.
3Measurement precision
If manual intervention is used to prioritize interactions, then accuracy is improved, but automation level decreases
Solution Approach 1:
The patent enables the system to self-determine interaction priorities by automatically measuring user interaction metrics and converting them into prioritization scores. This eliminates the need for manual prioritization while maintaining high accuracy, as the system uses actual user behavior data to make intelligent decisions about which regions to evaluate first.
Solution Approach 2:
The patent implements feedback by continuously measuring user interaction with interface regions and using this information to dynamically adjust prioritization. The system learns from actual usage patterns and adapts its evaluation strategy accordingly, achieving both high accuracy and full automation without manual intervention.
Data Source
AI summary
Performing an automated interaction with a computer software application by identifying, among a plurality of regions of an interface of a computer software application, a region for which a region-level measure exists of user interaction that occurred within the region of the interface, determining if the region-level measure meets or exceeds a predefined minimum level of user interaction, and performing an automated interaction with an element at least partly found within the region if the region-level measure meets or exceeds the predefined minimum level of user interaction.