Real-time User Interaction Tracking System
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing application software systems face challenges in providing personalized user interfaces that adapt to varying user abilities and experiences, leading to inefficiencies in user interaction and increased support costs due to difficulties in navigating complex applications.
Innovation Solution
A system that monitors user interactions with application software, tracks and processes activity histories to predict user actions, and modifies user experiences in real-time by assisting with features like technical support and interface modifications, ensuring seamless and efficient usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the system tracks and processes all user interactions in real-time, then user experience personalization is improved, but application performance is degraded
Solution Approach 1:
The system implements partial processing by selectively tracking and processing only a subset of user interactions rather than all interactions. The processor identifies and processes interactions that are most relevant for personalization while ignoring less critical ones, thereby achieving personalization benefits with reduced processing overhead that maintains application performance
Solution Approach 2:
The system extracts and separates the interaction processing function from the main application execution. By isolating the tracking and processing operations into a dedicated module that runs independently, the application's core performance is not impacted by the personalization processing, allowing both functions to operate optimally
2Measurement precision
If the system processes interactions frequently to obtain accurate activity history, then prediction accuracy is improved, but processing time is increased
Solution Approach 1:
The system implements periodic processing where the processor handles user interactions at scheduled intervals rather than continuously. This periodic approach maintains sufficiently accurate activity history for effective prediction while significantly reducing the total processing time and computational resource consumption compared to continuous processing
Data Source
AI summary
Some embodiments provide a system that monitors use of an application. During operation, the system uses the application to track a set of interactions between a set of users and the application without impacting the performance of the application. Next, the system stores the interactions as the interactions are detected by the application. Finally, for each user from the set of users, the system periodically processes a subset of the stored interactions associated with the user to obtain an activity history for the user, wherein the activity history is used to facilitate subsequent real-time use of the application by the user.