GUI Data Preloading via Pointer Prediction
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Solution Overview
Problem
Existing graphic user interface (GUI) systems fail to provide immediate responses to user selections, leading to delayed data loading times, as they do not effectively predict and preload necessary data before user input.
Innovation Solution
A data preloading method that predicts user intent by analyzing pointer position, movement speed, and gaze direction, preloading relevant data into a cache when a selection is likely, and accessing it immediately upon confirmation of the selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data is preloaded based on pointer position analysis, then GUI response speed is improved, but system complexity increases due to predictive algorithms
Solution Approach 1:
The system performs preliminary actions by preloading data into cache before the user actually selects an object. When the pointer hovers over or approaches a GUI object, the system predicts selection intent and loads the associated data in advance, so that when selection occurs, the response is immediate without waiting for data loading.
Solution Approach 2:
The system dynamically adjusts the preloading behavior based on real-time pointer position and movement analysis. The predictive algorithm continuously monitors pointer coordinates and calculates selection probability, dynamically deciding whether and what data to preload, making the system adaptive rather than static.
2Loss of time
If data preloading is performed based on pointer analysis, then data loading time is reduced, but energy consumption increases
Solution Approach 1:
The system applies partial action by selectively preloading only the data associated with GUI objects that have a high probability of being selected, rather than preloading all possible data. The pointer analysis algorithm calculates selection probability and triggers preloading only when the threshold is met, avoiding unnecessary energy consumption for objects that won't be selected.
3Measurement precision
If selection prediction is performed using multiple parameters (pointer position, movement speed, gaze), then prediction accuracy is improved, but computational complexity increases
Solution Approach 1:
The system segments the prediction process into distinct analytical components: pointer position analysis, movement speed analysis, and optionally gaze direction analysis. Each parameter is processed separately to determine its contribution to selection probability, allowing the system to use only the necessary parameters for a given scenario rather than always processing all parameters.
Data Source
AI summary
Provided is a data preloading method which improves the response speed of a user device by predicting whether a particular object provided on a graphic user interface (GUI) will be selected based on the position of a pointer before the particular object is selected by a user and preloading data that should be loaded when the particular object is selected.