Web Page Prediction via Context Analysis and Prefetching
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Solution Overview
Problem
Current web browsers lack the ability to predict and display web pages based on user context, such as location and browsing habits, leading to an inefficient browsing experience.
Innovation Solution
A system comprising a computer-readable storage medium, processor, and calculation module that predicts web pages by analyzing user context, including location, time, and browsing history, and displays the predicted pages, with the option to prefetch linked content to ensure uninterrupted browsing even when disconnected from a network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If web browsers display information only at requested URLs, then the browsing system remains simple and reliable, but the browsing efficiency and user experience deteriorate due to lack of prediction and context awareness
Solution Approach 1:
The patent implements prediction of web pages before the user actually requests them. The system analyzes current context (location, time, device) and browsing history to predict and prepare web pages in advance, so they are ready for immediate display when needed, eliminating waiting time and improving browsing efficiency
Solution Approach 2:
The browsing system performs self-service by automatically analyzing user context and browsing patterns to generate predictions without requiring explicit user input. The system serves itself by maintaining a history of browsing behavior and using it to autonomously determine what web pages the user is likely to visit next
2Reliability
If the system prefetches linked content, then connectivity is maintained during network disconnections, but energy consumption and memory usage increase
Solution Approach 1:
The system performs preliminary prefetching of linked content when the network is available and the device is connected. By loading content in advance during periods of network connectivity, the system ensures that content is ready for immediate display when the network disconnects, maintaining perceived connectivity and user experience without requiring continuous network access
Solution Approach 2:
The prefetching behavior is dynamic and adaptive rather than static. The system adjusts its prefetching based on current network conditions, battery status, and predicted user behavior. When energy is abundant and network is reliable, more aggressive prefetching occurs; when energy is constrained or network is unstable, prefetching is reduced or stopped
3Adaptability or versatility
If web browsers are regularly pointed to a few URLs, then the browsing system remains simple to operate, but adaptability and personalization deteriorate
Solution Approach 1:
The system provides personalized web page predictions automatically without requiring users to configure settings or manually input preferences. By analyzing browsing history and context self-service style, the system adapts to each user's unique patterns and provides customized predictions that feel tailored without any operational complexity from the user's perspective
Solution Approach 2:
The system implements feedback loops where user interactions with predicted web pages are continuously monitored and fed back into the prediction model. This feedback mechanism allows the system to learn from user behavior, refine its predictions, and improve adaptability over time while maintaining simple operation for the end user
Data Source
AI summary
For predicting web pages, a calculation module predicts a web page from a current context and displays the predicted web page.