Automated Website Quality Analysis via Contextual Segmentation
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Solution Overview
Problem
Websites often face challenges in identifying and addressing quality issues across multiple webpages, as existing methods lack efficiency in segmenting and analyzing similar issues, leading to repetitive and time-consuming tasks for website owners.
Innovation Solution
A system and method for automatically determining contextual segments in webpages and dynamically assessing issues within those segments, using segment criteria to group webpages with similar issues, allowing for quick fixes and improved user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If website owners manually review and fix quality issues across multiple webpages, then comprehensive quality assessment can be achieved, but the process becomes time-consuming and repetitive
Solution Approach 1:
The patent segments webpages into distinct contextual sections (headers, footers, content areas, navigation elements) and analyzes each segment independently. This allows the system to efficiently identify and group similar issues across multiple webpages without requiring manual review of entire pages, thereby maintaining comprehensive quality assessment while reducing time consumption.
Solution Approach 2:
The patent creates a standardized segment model that can be copied and applied across multiple webpages. Once a segment type is identified and analyzed on one webpage, the same segment criteria and issue detection methods are automatically applied to similar segments on other webpages, eliminating repetitive manual analysis while ensuring consistent quality assessment.
2Reliability
If website owners review all webpages individually to identify quality issues, then all issues can be detected, but the task becomes repetitive and inefficient
Solution Approach 1:
The patent merges the analysis of multiple webpages by grouping segments that are contextually similar across different pages. Issues are aggregated at the segment level rather than the individual webpage level, allowing the system to detect patterns and common problems across the entire website while maintaining high detection accuracy. This merging approach significantly improves productivity by reducing the number of individual review tasks.
Solution Approach 2:
The patent uses standardized segment definitions and issue detection rules that are copied and applied consistently across all webpages. This ensures reliable and accurate issue detection while automating the process, thereby improving both reliability and productivity simultaneously.
3Loss of information
If detailed segment analysis is performed on each webpage, then comprehensive quality insights are obtained, but the complexity of the analysis process increases
Solution Approach 1:
The patent divides webpages into standardized contextual segments (headers, footers, content areas, navigation) with predefined analysis rules for each segment type. This segmentation approach maintains comprehensive quality insight by analyzing all critical segments while reducing system complexity through standardized, reusable segment templates and consistent analysis methodologies across different webpage types.
Data Source
AI summary
Described herein are systems and methods for assessing website quality based on automated website analysis. A method can include identifying, by a computing system, a website to evaluate, retrieving code for webpages of the website from one or more web server systems that host the website, locally executing and interpreting the code to render the webpages as they would appear on client devices, identifying webpage segment criteria, analyzing the webpages to identify a subset of webpages that include a segment satisfying the webpage segment criteria, identifying a quality issue in the segment that is present in each webpage in the subset, determining a quantity of times the quality issue occurs across the subset of webpages, and providing information to a client device to cause the client device to present an indication of the issue and an indication of the quantity of times the issue occurs across the subset of webpages.