Content Retrofitting via Information Vectorization for Adaptive Training

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Solution Overview

Problem

Users often deviate from predetermined on-screen actions while completing tasks, leading to decreased productivity, but occasional deviations can increase efficiency, necessitating a system that incorporates these outliers into training and task execution requirements.

Innovation Solution

A system that uses information vectorization to analyze user interactions, identifies deviations and outliers, and generates modified video files by interleaving user-specific frames with standard interaction requirements, stored in a knowledge repository for retraining and domain-level updates.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If users follow predetermined interaction requirements, then task execution reliability is improved, but productivity decreases due to inability to incorporate efficient deviations

Engineering Contradiction:

Improvetask execution reliabilityVSAvoidproductivity

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system dynamically adjusts training content by identifying user deviations from predetermined interaction requirements and determining whether these deviations represent efficient outliers or errors. Based on this analysis, the system adapts training videos to incorporate proven efficient deviations while maintaining reliability for critical interactions.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system implements a feedback loop where user interactions are monitored, compared against predetermined requirements, and analyzed to identify patterns. Efficient deviations are fed back into the training material through content retrofitting, continuously improving both reliability and productivity.

Inventive Principle:

Principle #23Feedback

2Adaptability or versatility

If training content is updated to incorporate user deviations, then adaptability is improved, but training material complexity increases

Engineering Contradiction:

Improvetraining material adaptabilityVSAvoidtraining material complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system segments training content into modular video files with specific interaction requirements. Each deviation analysis and content retrofitting operation targets specific segments rather than overhauling entire training programs, managing complexity through structured modularity.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system changes parameters of existing training videos by selectively inserting or modifying specific frames and segments based on analyzed deviations. This approach adapts training content without recreating entire materials, maintaining manageability while improving adaptability.

Inventive Principle:

Principle #35Parameter changes

3Manufacturing precision

If all user deviations are corrected to meet interaction requirements, then manufacturing precision is improved, but loss of time increases due to retraining

Engineering Contradiction:

Improveinteraction precisionVSAvoidretraining time

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The system converts user deviations, which could be seen as errors, into beneficial training content by identifying efficient outliers. Instead of treating all deviations as mistakes requiring correction, the system leverages them to improve training relevance and reduce unnecessary retraining time.

Inventive Principle:

Principle #22Blessing in disguise (Convert harm into benefit)

Solution Approach 2:

The system applies partial correction by selectively addressing only those deviations that represent errors rather than efficient alternatives. This avoids excessive retraining on content that is already optimal, reducing time loss while maintaining necessary precision.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS11348617B1System for implementing content retrofitting using information vectorization

Publication Date: 2022.05.31 BANK OF AMERICA CORP

AI summary

Systems, computer program products, and methods are described herein implementing content retrofitting using information vectorization. The present invention is configured to retrieve a user interaction portfolio of a user associated with a completion of a first task; determine requirements associated with the first task; determine an interaction score associated with the user; determine a target interaction score associated with the first task; determine that the interaction score associated with the user is greater than the target interaction score associated with the first task; generate one or more second image frames based on at least the one of the one or more user interactions that did not meet the one or more interaction requirements; generate at least one modified video file based on at least the one or more second image frames; and store the at least one modified video file in a knowledge repository.