Tree-Like Cache Structure for Customized Web Page Retrieval
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Solution Overview
Problem
Conventional methods for providing customized web pages are inefficient, inflexible, and difficult to maintain, consuming large storage space and struggling with scalability as the number of user criteria increases, leading to poor performance and maintenance challenges.
Innovation Solution
A computer-implemented system using a tree-like data structure stored in cache, where nodes store identifiers referring to customized content entries, allowing for efficient retrieval and updating of customized web pages based on user information, reducing storage needs and complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional methods manually modify websites to customize for different users, then customization is achieved, but the process becomes tedious and time-consuming
Solution Approach 1:
The system pre-generates customized web pages for different user segments before users actually visit the website. User profiles with customization preferences are created in advance, and the web server automatically selects and assembles appropriate content based on these pre-defined profiles, eliminating the need for real-time manual customization.
Solution Approach 2:
The system enables automatic self-customization where the web server autonomously selects and assembles web page content based on user profiles and preferences without human intervention. The automated content assembly process allows the system to serve customized pages dynamically, freeing designers from manual modification tasks.
2Adaptability or versatility
If conventional approaches store customized content for each user, then customization is provided, but storage space consumption increases significantly
Solution Approach 1:
The system segments web page content into modular components that can be independently stored and recombined. Instead of storing complete customized web pages for each user, the system divides content into reusable segments organized by user characteristics and preferences, allowing efficient storage and dynamic assembly.
Solution Approach 2:
The system creates lightweight user profiles that contain only essential customization preferences and identifiers rather than duplicating entire customized web pages. These profile copies reference the actual content segments needed, dramatically reducing storage requirements while maintaining full customization capability.
3Measurement precision
If the number of criteria to differentiate between users increases, then more precise customization is achieved, but implementation difficulty and complexity increase
Solution Approach 1:
The system adds a hierarchical dimension to user differentiation by organizing multiple criteria into nested levels of user profiles. Instead of managing multiple independent criteria at the same level, the system structures them in hierarchical layers, allowing complex user segmentation through systematic organization rather than increasing horizontal complexity.
Solution Approach 2:
The system implements nested user profiles where broader user characteristics contain more specific sub-characteristics. This nested structure allows the system to handle multiple differentiation criteria by organizing them in concentric layers, where each level builds upon the previous one, simplifying the management of complex customization requirements.
4Adaptability or versatility
If conventional approaches retrieve customized content dynamically, then personalized pages are delivered, but retrieval complexity and processing time increase
Solution Approach 1:
The system pre-organizes content segments and user profiles before retrieval is needed. User profiles are pre-configured with preferred content types and characteristics, and content segments are pre-categorized and indexed. This preliminary organization enables rapid matching and retrieval during actual web page delivery without complex real-time processing.
Solution Approach 2:
The system segments both user profiles and content into manageable, independently processable units. This segmentation allows the retrieval process to work with small, focused data pieces rather than large monolithic structures, significantly improving retrieval speed and efficiency while maintaining personalization accuracy.
Data Source
AI summary
Computer implemented methods and systems are provided for providing customized web pages that are customized for each user. A database can store first entries each being configured to store user information for each user, and second entries each being configured to store an identifier and customized content for each user (or alternatively a way to retrieve such customized content). A tree-like data structure is stored in cache and includes nodes that each store an identifier that refers to one of the second entries. After log in, the server system retrieves user information associated with the particular user and uses it to retrieve a particular identifier stored by a particular node. Using a corresponding one of the second entries that includes the particular identifier, particular customized content for the particular user can be retrieved and sent to a user system where it is used to display a particular customized web page for that particular user.