Microapp Recommendation via Interaction Tracking
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Solution Overview
Problem
Current systems fail to efficiently streamline application functionality for users, as they often require launching full applications to perform tasks, which can be time-consuming and complex, especially when dealing with forms that have multiple interface elements.
Innovation Solution
A method and system that track user interactions with forms to determine a recommendation score for creating microapps, which involve enabling event handlers to detect changes and submissions, and using hash values to analyze variance in input values across multiple users, thereby identifying which interface elements to include in a streamlined microapp.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If full applications are launched to perform tasks, then complete functionality is available, but task completion time increases and system complexity increases
Solution Approach 1:
The patent segments full applications into smaller functional units called microapps. Each microapp performs a specific task (e.g., submitting a form, calculating totals) without requiring the entire application to launch. This segmentation reduces task completion time and system complexity while maintaining necessary functionality through modular design.
Solution Approach 2:
The patent extracts frequently used functionality from full applications into standalone microapps. By taking out specific tasks (form submission, calculations, data entry) and making them independently executable, the system eliminates the need to load entire applications for simple tasks, thereby reducing complexity and improving ease of operation.
2Productivity
If microapps are created to streamline functionality, then task completion time decreases, but system complexity increases due to tracking and analysis requirements
Solution Approach 1:
The tracking system operates autonomously by automatically monitoring user interactions with forms and microapps. Event handlers self-activate to detect changes, submissions, and user behavior patterns without requiring manual configuration or complex external monitoring infrastructure, thus improving productivity while minimizing added complexity.
Solution Approach 2:
The system transforms complex behavioral tracking data into simplified variance metrics by changing the parameter representation. Instead of tracking every individual interaction detail, the system converts data into variance values that capture essential usage patterns, reducing tracking complexity while maintaining analytical capability for productivity improvement.
3Adaptability or versatility
If user interactions are tracked to create microapps, then functionality streamlining improves, but data processing complexity increases
Solution Approach 1:
The patent transforms complex interaction data into simplified variance metrics that capture essential usage patterns. By changing the parameter representation from detailed interaction logs to aggregated variance values, the system improves microapp recommendation accuracy while reducing data processing complexity through dimensional reduction.
Solution Approach 2:
The system discards redundant interaction data that does not contribute to microapp creation decisions while recovering and retaining essential variance patterns. This selective data retention strategy improves recommendation accuracy by focusing on meaningful signals while reducing processing complexity by eliminating noise.
Data Source
AI summary
Disclosed is a system for tracking user interactions with an application to recommend creation of a microapp. The system determines a recommendation score for creating a microapp corresponding to a functionality of an application based on at least one of the amount of time users spend interacting with the application, the number of interface elements of the application that the user changes, and the input values provided by the users. The system uses interactions corresponding to multiple different users to determine the recommendation score. The system may also recommend an interface element to be included in the microapp. The recommendation score is provided to an administrator, who may use the information to create a microapp.