Web Link Preloading via Trigger Area Prediction
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Solution Overview
Problem
Users experience frustration due to long loading times and progressive rendering of web content when navigating between links, leading to a poor user experience as the content appears broken until fully loaded.
Innovation Solution
Preloading content based on user behavior prediction by identifying trigger areas and caching resources before the user selects a link, allowing seamless transitions without latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If content is loaded progressively when user clicks a link, then the document can be rendered partially, but the content appears broken and loading time is extended
Solution Approach 1:
The system performs preliminary action by predicting which link the user will click next and preloading the associated content before the actual click occurs. This is achieved by detecting user interactions with trigger areas, predicting the intended link, and initiating resource download in advance, so that when the user actually clicks, the content is already ready for immediate display without appearing broken or requiring progressive loading.
2Loss of time
If content is preloaded before link selection, then latency is eliminated and transition is seamless, but resources are consumed before user needs them
Solution Approach 1:
The system performs preliminary action by predicting which link the user will click next and preloading the associated content before the actual click occurs. This is achieved by detecting user interactions with trigger areas, predicting the intended link, and initiating resource download in advance, so that when the user actually clicks, the content is already ready for immediate display without appearing broken or requiring progressive loading.
Solution Approach 2:
The system uses feedback from detecting user interactions with trigger areas to refine link prediction accuracy. By continuously monitoring user behavior patterns and comparing predicted links against actual user selections, the system improves its prediction model, thereby reducing unnecessary preloading and optimizing resource consumption while maintaining seamless transitions.
3Ease of operation
If standard link clicking behavior is used, then user control is maintained, but loading delay causes broken appearance and frustration
Solution Approach 1:
The system performs preliminary action by predicting which link the user will click next and preloading the associated content before the actual click occurs. This is achieved by detecting user interactions with trigger areas, predicting the intended link, and initiating resource download in advance, so that when the user actually clicks, the content is already ready for immediate display without appearing broken or requiring progressive loading.
Data Source
AI summary
A preloading tool facilitates efficient loading for content associated with links in a web document. An index containing links for a current page is created. The index includes coordinates of the links and trigger area coordinates of a trigger area for each link. When a user interaction is detected in a trigger area indicating the user may wish to navigate to additional content (i.e., the predicted link), standard click behavior for the predicted link is disabled. Resources required to render the content (i.e., the new page) for the predicted link begin downloading and are cached. Once the user actually selects the link, the transition from the current page to the new page is accomplished without the new page appearing broken. In some instances, certain links are excluded from the index and/or target attributes point to one or more containers that will be updated by one or more of the links.