DOM Tree Analysis for Web Page Navigation Region Identification
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Solution Overview
Problem
Conventional methods for identifying navigation regions in web pages using assistive technologies are inefficient due to reliance on visual content rendering, which does not match screen reader experiences, and often result in inaccurate calculations and computationally expensive machine-learning approaches.
Innovation Solution
A method based on document object model (DOM) analysis that identifies navigation regions by analyzing features such as interactive elements, content regions, and landmarks, representing them in a tree structure to determine link density, reading order, and main content roots, enabling effective region navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional approaches use page renderings to identify navigation regions, then visual layout information is available, but the content does not match what screen reader users experience and generation is difficult
Solution Approach 1:
The patent uses the DOM tree as an intermediary representation between the web page content and the navigation region identification process. Instead of directly analyzing visual renderings or raw HTML, the system processes the DOM tree structure, which provides an abstracted view that matches screen reader experience while being computationally accessible. This intermediary representation resolves the contradiction by decoupling the analysis from both visual rendering complexity and raw content disorganization.
2Reliability
If machine-learning clustering algorithms are used to identify navigation regions, then comprehensive analysis is achieved, but computational cost is high and clustering results are difficult to label
Solution Approach 1:
The patent replaces complex machine-learning clustering algorithms with a rule-based system that operates on DOM tree characteristics. Instead of using computationally expensive statistical clustering methods, the system applies deterministic rules based on DOM node properties, link density, and hierarchical structure. This substitution maintains comprehensive analysis capability while dramatically reducing computational overhead and eliminating the labeling difficulty associated with unsupervised clustering results.
3Area of stationary object
If web browsers capture complete screenshots for analysis, then full web page content is available, but stitching screenshots together is complicated by scrolling-induced design changes
Solution Approach 1:
The patent creates a virtual copy of the web page content through the DOM tree structure, which represents the entire page hierarchy without requiring physical capture of visual content. This virtual representation allows complete content analysis while avoiding the stitching problem entirely, as the DOM tree naturally represents the full page structure including off-screen content through its hierarchical node relationships.
4Loss of information
If CSS computed values are used to calculate navigation regions, then rendering information is accessible, but calculations are inaccurate due to overflow and content filling issues
Solution Approach 1:
The patent extracts the essential structural information from CSS computations by focusing on DOM node properties and hierarchical relationships rather than relying on computed rendering values. The system extracts link density, node depth, and hierarchical position from the DOM tree, separating the structural analysis from the rendering-specific calculations that cause accuracy problems with overflow and content filling.
Data Source
AI summary
A method for facilitating identification of navigation regions in a web page based on document object model (DOM) analysis is provided. In one embodiment, the method includes analyzing the web page for features. The features include at least one of: interactive elements, content regions, link region roots, or landmarks. The method also includes representing the features in a tree structure and analyzing the tree structure for a link density to identify non-main landmarks, a reading order, and main content roots. The method further includes enabling a region navigation for the web page based on the identified non-main landmarks, reading order, and main content roots.