Navigation Prediction System Prerendering Web Content
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Solution Overview
Problem
Current high-speed Internet services still result in significant delays when users navigate web pages, leading to lost productivity due to the time spent waiting for content to load.
Innovation Solution
A method and system that predicts user navigation events by analyzing navigation history, text entry, and cursor position to prerender content likely to be selected next, thereby reducing wait times by preemptively requesting content from the network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If content is prerendered in advance based on navigation prediction, then user wait time is reduced, but system resources (memory, processing power, network bandwidth) are consumed
Solution Approach 1:
The system performs preliminary actions by prerendering web pages before users actually navigate to them. The navigation prediction module analyzes user behavior patterns, navigation history, and current page context to identify likely next destinations, then preemptively requests and renders these pages in the background, so when users click links, the content is already prepared and displays instantly.
Solution Approach 2:
Instead of prerendering all possible navigation destinations (excessive action), the system selectively prerenders only the most probable next pages based on prediction confidence thresholds. This partial action approach balances resource consumption with user experience improvement by focusing computational resources on high-probability predictions only.
2Measurement precision
If navigation history data is collected and stored for prediction, then prediction accuracy is improved, but user privacy is compromised
Solution Approach 1:
The system extracts only the essential navigation pattern information needed for prediction while removing or anonymizing personally identifiable information. Navigation history data is processed to extract behavioral patterns (click sequences, time stamps, page transitions) without storing sensitive user identifiers, achieving prediction accuracy while protecting privacy.
Solution Approach 2:
The patent introduces an intermediary processing layer that acts as a mediator between raw navigation data and the prediction algorithm. This intermediary anonymizes and aggregates navigation history data, transforming identifiable user behavior into generalized patterns that maintain prediction accuracy while eliminating privacy risks associated with storing individual user information.
Data Source
AI summary
A method and system for predicting a next navigation event are described. Aspects of the disclosure minimize the delay between a navigation event and a network response by predicting the next navigation event. The system and method may then prerender content associated with the next navigation event. For example, the method and system may predict a likely next uniform resource locator during web browsing to preemptively request content from the network before the user selects the corresponding link on a web page. The methods describe a variety of manners of predicting the next navigation event, including examining individual and aggregate historical data, text entry prediction, and cursor input monitoring.