Schema Generation System for Automated Intervention Filtering
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Solution Overview
Problem
Manual filtering of potential interventions in industries is time-consuming, error-prone, and complex, leading to inefficiencies and waste due to the complexity of identifying suitable interventions for deployment.
Innovation Solution
An apparatus and method for generating a schema using a processor and memory to display a graphical control interface, receive a criterion element, identify significant terms, train a machine-learning model, and produce a schema to reduce decision-making complexity, involving a content field window, machine-learning module, and decision trees.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual filtering of potential interventions is performed, then human judgment and flexibility are maintained, but time consumption and error rates increase
Solution Approach 1:
The patent introduces an automated filtering system with machine learning models as an intermediary between the potential interventions and human reviewers. The system automatically filters interventions based on learned patterns from training data, handling routine cases without human intervention while allowing human reviewers to focus on complex cases that require judgment, thus reducing time consumption while maintaining reliability
Solution Approach 2:
The patent replaces the manual mechanical filtering process with an automated computational system. Machine learning models and algorithms substitute human manual review for routine filtering tasks, automatically analyzing and categorizing potential interventions based on predefined criteria and learned patterns, thereby eliminating time-consuming manual operations while maintaining consistent accuracy
2Reliability
If manual filtering of potential interventions is performed, then human expertise is applied, but complexity and error rates increase
Solution Approach 1:
The patent segments the filtering process into distinct automated stages: initial automated filtering using machine learning models, identification of cases requiring human review, and specialized processing for complex cases. This segmentation reduces overall process complexity by automating routine segments while maintaining human expertise for complex segments, thereby improving reliability without increasing overall system complexity
3Productivity
If automated filtering systems are implemented, then time efficiency and consistency improve, but adaptability and handling of novel cases may worsen
Solution Approach 1:
The patent implements feedback mechanisms where the automated filtering system continuously learns from new data and outcomes. The system receives feedback from human reviewers and actual intervention outcomes, using this information to retrain and improve its models, thereby maintaining high productivity while gradually improving adaptability to novel cases through continuous learning and model updates
Data Source
AI summary
An apparatus and method for generating a schema, the apparatus comprising at least a processor and a memory communicatively connected to the at least a processor, the memory containing instructions configuring the at least a processor to display, at a graphical control interface, a content field window, receive, as a function of the content field window, a criterion element, and generate a schema as a function of the criterion element.