Web Element Matching for Tutorial Accuracy
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Solution Overview
Problem
Interactive tutorials for digital adoption platforms face challenges in maintaining accuracy and efficiency due to frequent changes in software platforms or websites, leading to time-consuming and costly manual updates, and existing solutions either rely on unique identifiers that are inconsistent or require labor-intensive special identifier tags.
Innovation Solution
A method that analyzes over 50 attributes and relationships of HTML elements to automatically update tutorials by generating a similarity metric, using cluster and k-NN analysis to determine the most likely matching elements, eliminating the need for unique identifiers and reducing manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual updates are used to maintain tutorial accuracy after website changes, then tutorial reliability is maintained, but maintenance time and cost increase significantly
Solution Approach 1:
The system performs self-service by automatically detecting website element changes and updating tutorial references without human intervention. The tutorial system monitors itself for obsolescence and self-corrects by identifying and mapping to updated elements, eliminating the need for manual maintenance while preserving accuracy.
Solution Approach 2:
The system implements feedback mechanisms by continuously comparing tutorial element references against the current website state. When discrepancies are detected (indicating website changes), the system receives feedback about the changes and automatically adjusts tutorial references to maintain accuracy.
2Ease of operation
If unique identifiers are used to track website elements, then element matching is simplified, but consistency and reliability of matching decrease
Solution Approach 1:
The system transitions from relying on single unique identifiers to using multiple attributes and relationships as parameters for element identification. By considering various characteristics (type, class, relationships to other elements) simultaneously, the system achieves more reliable and consistent matching that adapts to website changes.
Solution Approach 2:
The system creates a composite identification approach by combining multiple element attributes and relationships into a unified matching criterion. This composite method is more robust than single-identifier approaches, maintaining both simplicity and consistency in element matching.
3Measurement precision
If special identifier tags are added to website elements for tutorial tracking, then tutorial element identification becomes precise, but website complexity and manual effort increase
Solution Approach 1:
The system extracts identification information from existing website attributes and relationships rather than adding special identifier tags. By utilizing already-present HTML attributes and element relationships, the system achieves precise element identification without increasing website structural complexity or requiring manual tag addition.
Solution Approach 2:
The system makes existing website attributes and relationships serve multiple functions: both their original purposes and element identification for tutorials. This multi-functionality eliminates the need for separate identifier tags, reducing complexity while maintaining identification precision.
Data Source
AI summary
Online tutorials for websites or software platforms can become out of date quickly once a website or platform has a minor update. Embodiments of the present invention fix this problem by automatically mapping website elements from the original tutorial to elements of the updated website by calculating and determining similar non-exact matches to those elements as the website changes. This gives designers of websites flexibility to perform maintenance and updates to their websites without regularly reprogramming their tutorials ensuring a higher accuracy of educational material for the end-user.