Defect Record Classification via Plain Language Mapping
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Solution Overview
Problem
The existing defect classification methodologies, such as the DRM taxonomy, are time-consuming and require extensive training, making it difficult for untrained users to classify defect records effectively, especially when dealing with plain language phrases in various languages.
Innovation Solution
A method and system that maps plain language phrases to a taxonomy, allowing users to classify defect records using a user-friendly interface, where plain language phrases are translated into DRM taxonomy, enabling real-time categorization and accurate classification regardless of the user's location or language proficiency, using a natural language engine and translation tool.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If DRM taxonomy is used for defect classification, then classification accuracy is improved, but learning time and operational complexity increase
Solution Approach 1:
The patent introduces a translation tool as an intermediary between the user and the DRM taxonomy. The tool automatically translates plain language defect descriptions into DRM taxonomy classifications, eliminating the need for users to learn the complex taxonomy while maintaining accurate classification. The translation tool mediates the interaction by handling the complexity internally and presenting a simplified interface to users.
2Measurement precision
If DRM taxonomy is used for defect classification, then classification accuracy is improved, but device complexity increases
Solution Approach 1:
The patent extracts the complexity of DRM taxonomy from the user interface and relocates it to the translation tool's internal processing. The complex taxonomy structure is taken out from the direct user interaction layer and embedded within the translation mechanism, allowing the classification system to maintain high accuracy while the user interface remains simple and intuitive.
3Ease of operation
If plain language phrases are accepted directly, then ease of operation is improved, but classification accuracy deteriorates
Solution Approach 1:
The patent replaces the mechanical process of manual taxonomy learning and application with an automated translation system. Instead of requiring users to manually map defects to taxonomy categories (a complex mechanical process), the system uses automated translation technology to convert plain language descriptions into accurate taxonomy classifications, substituting human cognitive effort with computational processing.
Data Source
AI summary
An approach to classify different defect records by mapping plain language phrases to a taxonomy. The approach includes a method that includes receiving, by at least one computing device, a defect record associated with a defect. The method further includes receiving, by the least one computing device, a plain language phrase or word. The method further includes mapping, by the least one computing device, the plain language phrase or word to a taxonomy. The method further includes classifying, by the least one computing device, how the defect was at least one of detected and resolved using the taxonomy.