Cloud Website Recommendation via Terminal Access Statistics
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Solution Overview
Problem
Current website recommendation systems in browsers rely on local cookies, which fail to recommend non-cookie websites and have high update costs, leading to poor coverage and freshness, and existing cloud-based systems use universal search engines, resulting in low relevance and quality recommendations.
Innovation Solution
A system that captures and stores terminal access statistics to recommend cloud websites based on accessed frequency, using a sorting unit, capturing unit, and query processing unit to provide relevant and fresh recommendations by querying stored data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If local cookies are used for website recommendation, then the system is simple to implement, but the coverage and freshness of recommended websites deteriorates
Solution Approach 1:
The patent transitions from local storage (one-dimensional, terminal-side only) to cloud-based storage (adding a new dimension, server-side centralized storage). This allows the system to maintain simplicity at the terminal while achieving comprehensive coverage and freshness through centralized cloud storage that aggregates data from multiple terminals.
Solution Approach 2:
The patent introduces a server as an intermediary between terminals and the recommendation system. The server acts as a mediator that collects terminal access statistics, builds website libraries, and provides recommendation data to terminals, resolving the contradiction by centralizing complex functions while keeping terminal devices simple.
2Reliability
If universal search engine is used for cloud website recommendation, then the coverage of recommended websites is improved, but the relevance and quality of recommendations deteriorates
Solution Approach 1:
The patent applies local quality by making different parts of the recommendation system serve different functions: the server-side provides comprehensive coverage through centralized storage, while the terminal-side provides personalized, relevant recommendations based on local access statistics. This division allows both coverage and relevance to be optimized in their respective domains.
Solution Approach 2:
The patent implements preliminary action by pre-building a website library on the server side with comprehensive website data before users make queries. This pre-processing ensures comprehensive coverage is available, while the actual recommendation relevance is determined later based on specific user access patterns and query context.
3Reliability
If website library is updated frequently from cloud, then the freshness of recommended websites is improved, but the update cost increases
Solution Approach 1:
The patent merges the website library storage function to the server side, combining data collection, storage, and update operations in one centralized location. This eliminates the need for each terminal to independently update local libraries, reducing redundant update operations and associated costs while maintaining fresh data through centralized management.
Solution Approach 2:
The system implements self-service through automatic data collection from terminal access statistics and automated library building on the server side. The server automatically updates the website library based on aggregated terminal data without requiring manual intervention or frequent synchronized updates to each terminal, reducing update costs while maintaining freshness.
Data Source
AI summary
The present invention discloses a method and system for recommending cloud websites based on terminal access statistics, wherein, the method mainly comprises: storing websites accessed by a terminal, and sorting the websites according to the accessed frequency by the terminal; capturing corresponding website descriptive information according to a website sorting result; storing the websites and corresponding descriptive information to a cloud storage medium; and when receiving a query request, querying the stored websites and corresponding website descriptive information according to the query keywords in the query request, returning a query result, and returning one or more websites whose frequency ranks on the top in the query result as recommended items. The present invention calculates the popularity of websites and sorts the websites based on the statistics about access behaviors, thereby significantly improving the quality and relevance of the recommended result.