Software Workflow Content Update Detection With Vector Tagging
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Solution Overview
Problem
Organizations face challenges in maintaining up-to-date content for software applications due to software updates, requiring manual and subjective human efforts that are cumbersome and prone to error, especially when using video content for training or educating stakeholders.
Innovation Solution
A method and system using vector tagging to objectively detect content updates by creating embeddings for content stages, comparing them with new content, and simulating workflows to identify changes, thereby reducing computing resource consumption and increasing processing speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual methods are used to identify and update software content, then human judgment can be applied, but the process becomes cumbersome, time-consuming, and prone to human error
Solution Approach 1:
The patent replaces manual mechanical processes with an automated computer vision system. The system uses image processing algorithms to automatically capture screenshots of software applications, compare them across different versions, and detect changes without human intervention. This substitution eliminates human error and significantly reduces the time required for content update detection.
Solution Approach 2:
The system enables self-service by allowing the content management system to automatically detect and identify updates without requiring manual review. The automated comparison algorithm independently analyzes software screenshots, generates change detection results, and triggers content updates autonomously, freeing human operators from repetitive manual tasks.
2Measurement precision
If comprehensive content monitoring is implemented to ensure accuracy, then detection precision improves, but computing resource consumption increases
Solution Approach 1:
The patent segments the software application interface into multiple regions of interest (ROIs) rather than analyzing the entire screenshot uniformly. By dividing the interface into relevant sections (e.g., buttons, menus, key display areas), the system focuses computational resources only on areas where changes are likely to occur, maintaining high detection precision while reducing overall computing resource consumption.
Solution Approach 2:
The system applies different analysis depths to different regions of the software interface based on their importance. Critical areas receive more rigorous analysis while less important areas use lighter processing. This local quality approach ensures that detection precision is maintained for key functional elements while minimizing unnecessary computational expenditure on peripheral or static regions.
Data Source
AI summary
A system and method for detecting content updates. A method includes creating a plurality of embeddings based on a first set of content demonstrating a workflow for using a software application, wherein each of the plurality of embeddings corresponds to a respective content stage of a plurality of content stages of the first set of content, wherein each content stage is a portion of the first set of content representing a respective part of the workflow for using the software application; and detecting a content update trigger based on the plurality of embeddings, wherein detecting the content update trigger further comprises comparing the first set of content to a second set of content with respect to the plurality of embeddings.