Web Resource Segmentation via Multi-Faceted Analysis
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Solution Overview
Problem
Existing segment identification algorithms for web content on mobile devices are inefficient due to reliance on HTML structure alone, failure to account for microstructure, and poor handling of poorly written HTML, leading to suboptimal segmentation and increased resource usage on mobile devices.
Innovation Solution
A system that analyzes web resources from multiple facets, encoding information as weights on document nodes and using geometry and layout trees to identify and refine segments, allowing for real-time segmentation on mobile devices and improving user experience by reducing download times and resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing segment identification algorithms rely only on HTML structure, then the algorithm complexity is low, but the segmentation precision is poor
Solution Approach 1:
The patent merges multiple analysis dimensions (HTML structure, CSS styles, document microstructure, and layout geometry) into a unified segmentation algorithm. This combination allows the system to achieve high segmentation precision by considering both semantic markup and visual presentation, while the modular architecture manages complexity through organized integration of different analysis components.
Solution Approach 2:
The segmentation algorithm uses a composite approach by integrating multiple types of information (structural HTML tags, CSS styling data, microstructural patterns, and geometric layout properties) similar to how composite materials combine different substances to achieve superior properties. This multi-faceted analysis creates a robust segmentation system that overcomes the limitations of any single analysis method.
2Productivity
If the system serves complete web pages to mobile devices, then the user can access all content, but the download time increases and resource usage increases
Solution Approach 1:
The system extracts and identifies specific segments within web pages that are most relevant to mobile users based on multiple analysis dimensions. By separating identified segments from the complete page, the system enables selective content delivery, serving only the necessary portions to mobile devices and thereby reducing download time and resource consumption while maintaining content quality.
Solution Approach 2:
The patent applies segmentation to divide web pages into meaningful, independently deliverable units based on structural, stylistic, and geometric analysis. This segmentation enables the system to serve discrete content portions to mobile devices rather than complete pages, improving content delivery efficiency by transmitting only what is necessary while reducing download time and bandwidth usage.
3Measurement precision
If the system performs detailed analysis of web resources from multiple facets, then the segmentation accuracy improves, but the processing time increases
Solution Approach 1:
The system performs preliminary analysis of web resources by pre-processing and indexing HTML structure, CSS styles, and microstructural elements before segmentation is actually needed. This preliminary action prepares the data in advance, allowing the detailed multi-faceted analysis to proceed more efficiently when segmentation is required, thereby reducing actual processing time while maintaining high segmentation accuracy.
Solution Approach 2:
The patent replaces traditional sequential mechanical analysis with a parallel processing approach that simultaneously evaluates multiple facets (HTML structure, CSS styles, microstructure, geometry). This substitution of the analysis mechanism allows detailed multi-dimensional examination to occur without linearly increasing processing time, as computations are performed concurrently rather than in sequence.
Data Source
AI summary
A robust, lightweight, bottom-up segmentation method for Internet content. According to the present invention, individual segments are created based upon weights assigned according to document structure and markup elements and semantics. Smaller segments are then merged into larger segments by determining which portions of the content page are related to each other. The remaining segments are then intelligently divided based upon device constraints.