Web Page Target Object Identification via Rendering Instruction Parsing
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Solution Overview
Problem
Current methods for identifying target objects on web pages are inefficient, as they rely on manual assessment and lack automated verification processes, making it difficult to accurately distinguish between different types of web page elements such as logos, maps, banners, and advertisements.
Innovation Solution
A method and apparatus that utilize predetermined rules based on rendered object characteristics and code features to identify target objects on a web page, involving parsing rendering instructions, rendering the web page, and executing a verification process to confirm the target object, which includes applying rules to determine likelihood parameters indicating the probability of the object's identity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual assessment methods are used to identify target objects on web pages, then identification accuracy may be maintained through human judgment, but identification efficiency and automation level deteriorate significantly
Solution Approach 1:
The system enables automated self-identification of target objects by having the browser independently parse rendering instructions, extract object candidates, and verify them through rule-based validation without requiring manual human assessment for each object
Solution Approach 2:
The patent replaces manual human assessment (mechanical system) with an automated computational system that uses rendering instruction parsing, object candidate extraction, and rule-based verification to identify target objects programmatically
2Reliability
If comprehensive verification processes are implemented to accurately distinguish between different web page elements, then identification reliability improves, but system complexity increases
Solution Approach 1:
The verification process is segmented into distinct modular stages: rendering instruction parsing, object candidate extraction based on specific tags and attributes, and rule-based validation. Each stage handles a specific aspect of identification, making the overall complex process manageable and maintainable
Solution Approach 2:
The system uses parameter-based verification by extracting specific attributes (tags, classes, IDs, dimensions, positions) from rendering instructions and comparing them against predetermined rules. This parameter-driven approach enables reliable differentiation between object types through quantitative criteria rather than complex qualitative analysis
3Productivity
If automated rule-based verification is applied to rendered web page objects, then identification speed and automation level improve, but measurement precision may deteriorate due to difficulty in accurately determining rendered object characteristics
Solution Approach 1:
The system performs preliminary extraction of object characteristics directly from the rendering instructions (HTML/CSS code) before the objects are rendered. By parsing tags, classes, IDs, and style attributes from the source code, the system obtains precise characteristic data without relying on potentially imprecise post-rendering analysis
Solution Approach 2:
The patent uses rendering instructions (HTML/CSS code) as an intermediary between the web page source and the identified target objects. This intermediary layer provides structured, machine-readable characteristics that bridge the gap between automated processing needs and precise object identification
Data Source
AI summary
The methods and systems described herein relate to identifying a target object on a web page by receiving rendering instructions associated with the web page, parsing the rendering instructions to identify a target object candidate amongst the web page elements; rendering the web page based on the rendering instructions, executing a verification process to confirm that the target object candidate is the target object, applying a set of predetermined rules to the rendered version of the target object candidate and assigning a likelihood parameter indicative of a probability of the target object candidate being the target object. Other embodiments of the verification process are also disclosed herein.