Visual Document Object Model Generation for Markup Processing
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Solution Overview
Problem
Analyzing network-accessible documents, such as web pages, is resource-intensive and time-consuming, preventing developers from processing a large number of documents efficiently.
Innovation Solution
A computer-implemented technique that generates Visual Document Object Models (VDOMs) from markup-language documents, allowing for the creation of transformation logic that converts new documents into VDOMs without activating links, thereby reducing the need for resource-intensive link retrieval and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If links in markup-language documents are activated and linked information is retrieved and processed, then complete visual layout information is obtained, but computational resources and processing time increase significantly
Solution Approach 1:
The system performs preliminary actions by generating VDOMs from a sample set of documents and extracting transformation logic in advance. This pre-computed transformation logic is then reused to process new documents without needing to activate links, thereby achieving complete visual layout information while maintaining high processing speed and resource efficiency.
2Reliability
If links are activated and linked information is retrieved for every new document, then accurate visual appearance is achieved, but the process becomes resource-intensive and time-intensive
Solution Approach 1:
The system creates a simplified copy of the document structure in the form of a VDOM that captures the essential visual layout information without requiring the original linked resources. This copy is generated using pre-extracted transformation logic that encodes the relationship between markup elements and their visual representation, eliminating the need to retrieve actual linked content while maintaining visual accuracy.
3Productivity
If transformation logic is generated based on sampled documents, then processing of new documents becomes efficient, but the transformation logic must generalize from limited samples
Solution Approach 1:
The system extracts transformation logic that serves multiple functions: it captures the relationship between markup elements and visual layout, generalizes patterns from sample documents to new documents, and enables efficient processing across diverse document types. The transformation logic acts as a universal translator that adapts to different documents without requiring document-specific link activation.
Data Source
AI summary
A technique is described herein that receives a set of markup-language documents (e.g., HTML documents). The technique produces a set of object-model representations (VDOMs) based on the set of markup-language documents. For a given markup-language document, the producing operation involves accessing and processing information that is linked to the markup-language document. Each object-model representation also includes visual layout information that specifies a visual appearance of a page that would be produced upon display of the markup-language document by a browser application. The technique then generates transformation logic based on the set of markup-language documents and their corresponding VDOMs. The transformation logic, when applied to a new markup-language document, converts the new markup-language document into a corresponding VDOM without retrieving at least some information identified by links (if any) in the new markup-language document.