Webpage Preloading Policy Adaptation via Historical Data Analysis
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Solution Overview
Problem
Existing webpage preloading methods lack flexibility due to fixed rules for predicting target webpages, leading to lower accuracy and requiring manual updates, and traditional plug-in systems in mobile terminals are inflexible and unstable due to tight coupling between applications and plug-in systems.
Innovation Solution
Implement a method for webpage preloading that dynamically updates policies based on historical data, including access information and cache state, and introduce a plug-in system with an independent engine module and adaption module to enhance flexibility and stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If fixed rules are used for predicting target webpages to preload, then the preloading system is simple to implement, but the flexibility and accuracy of webpage prediction deteriorates
Solution Approach 1:
The patent applies dynamics by transitioning from static fixed rules to dynamic rule generation. The system automatically generates preloading rules based on real-time user behavior data, allowing the rules to adapt and evolve over time. This resolves the contradiction by making the system flexible enough to handle changing user patterns while maintaining automated operation without manual rule setting.
Solution Approach 2:
The preloading system performs self-service by automatically generating and optimizing its own preloading rules based on user behavior analysis. Instead of requiring manual configuration or external control, the system learns from user interactions and autonomously adjusts its prediction algorithms, thereby achieving both simplicity in operation and flexibility in adaptation.
2Ease of operation
If manual rule setting is used for webpage preloading, then the system is easy to control, but the responsiveness to changing user behavior deteriorates
Solution Approach 1:
The patent implements feedback mechanisms where user behavior data is continuously collected and fed back into the rule generation system. This closed-loop feedback allows the system to detect changes in user patterns and automatically update preloading rules in real-time, eliminating the time lag associated with manual rule updates while maintaining ease of operation through automated processes.
3Reliability
If plug-in system is tightly coupled with application, then the system is stable and reliable, but the flexibility and ease of development deteriorates
Solution Approach 1:
The patent applies segmentation by dividing the plug-in system into independent modules that can be developed, loaded, and executed separately from the main application. This modular segmentation maintains system stability through structured interaction protocols while significantly reducing development complexity, as each module can be optimized and updated independently without affecting the entire system.
4Ease of manufacture
If traditional plug-in system architecture is used, then the system is easy to implement, but the flexibility and stability of application programs deteriorates
Solution Approach 1:
The patent implements universality by creating a plug-in system architecture that can accommodate multiple types of applications and functions through a common interface framework. This universal design allows diverse applications to be integrated into the same platform without requiring custom implementation details, thereby maintaining ease of implementation while significantly enhancing flexibility and adaptability across different application scenarios.
Data Source
AI summary
Embodiments of the present disclosure disclose a method and a device for webpage preloading. The method includes: conducting webpage preloading according to a current preloading policy, in which the preloading policy includes: a preloading time range, a preloading region, a preloading page depth, and an available caching space for preloading; counting historical data within a pre-set time period, in which the historical data includes: information about an accessed webpage, information about a preload webpage, and state information of a local cache; and updating the preloading policy based on the historical data. In the present disclosure, by way of counting the preloading historical data within a pre-set time period, and based on the changes in the historical data, the preloading policy is automatically updated, so that the preloading policy can adapt to network and user access conditions in real time, thereby improving the hit accuracy of webpage preloading.