Webpage Pre-reading via User Similarity Prediction
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Solution Overview
Problem
Existing webpage pre-reading methods are inefficient for predicting next webpages on unordered content pages and can occupy cache space, leading to slow performance on smart terminals.
Innovation Solution
A method that analyzes visiting information from multiple users to determine similarity values and predicts target webpages likely to be accessed by similar users, pre-loading these pages into the local cache to enhance browsing speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If the second type webpage pre-reading method requests pre-reading a large amounts of data of multiple webpages potentially to be browsed, then the webpage loading speed is improved, but the local cache space is occupied and terminal performance is degraded
Solution Approach 1:
The patent applies local quality by differentiating between different user types (first type users who frequently access webpages and second type users who access webpages infrequently) and applying different pre-reading strategies to each. First type users receive aggressive pre-reading of multiple webpages while second type users receive minimal pre-reading, optimizing cache usage for each user segment's actual needs
Solution Approach 2:
The patent implements preliminary action by pre-reading webpage data before users actually request it. The system proactively loads webpage content into cache based on user classification and predicted access patterns, so that when users do access webpages, the data is already available locally, eliminating loading delays
2Measurement precision
If the first type webpage pre-reading method uses keywords to determine next webpages, then the pre-reading accuracy is improved for linked webpages, but it cannot predict webpages on unordered content pages such as news pages
Solution Approach 1:
The patent achieves universality by creating a multi-functional pre-reading system that handles both hyperlink-based navigation (first type webpages) and unordered content pages (second type webpages) through different strategies. The system universally serves all webpage types by selecting appropriate pre-reading methods based on webpage structure analysis
Solution Approach 2:
The patent applies segmentation by dividing webpage pre-reading into two distinct approaches: one for hyperlink-structured webpages where keyword-based next page prediction works well, and another for unordered content pages where sequential or random pre-reading is more appropriate. This segmentation allows each method to be optimized for its specific webpage type
3Productivity
If the system pre-reads multiple webpages to improve user experience, then the webpage access speed is improved, but the terminal performance is degraded due to limited resources
Solution Approach 1:
The patent implements partial action by pre-reading only a subset of webpages based on user classification. First type users receive extensive pre-reading of multiple webpages while second type users receive minimal pre-reading, ensuring that computational resources are partially applied only when necessary to achieve performance improvements
Data Source
AI summary
A method is provided for webpage pre-reading. The method includes obtaining visiting information during a period of time for multiple webpages of each user from a plurality of users including a current user; determining respective similarity values between the current user and the plurality of users based on the visiting information; determining one or more most-similar users based on the similarity values; and when the current user is browsing a current webpage, predicting a target webpage to be accessed by the most-similar users as a target webpage for the current user and pre-reading the target webpage.