Technical Specification Matching via Feature Importance Weighting
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Solution Overview
Problem
Existing technologies face challenges in efficiently matching technical specifications between consumers and manufacturers due to differences in language and complexity in technical descriptions, requiring technically trained personnel and scattered information across multiple sources.
Innovation Solution
A method utilizing trained language models and neural networks to identify and calculate the importance of technical features, enabling the calculation of matching scores between consumer specifications and vendor descriptions, thereby facilitating the identification of suitable products.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual matching of technical specifications is performed by technically trained personnel, then matching accuracy is improved, but labor cost and time consumption increase
Solution Approach 1:
The patent replaces the mechanical manual review process with an automated NLP-based system. The system uses trained language models to extract technical features from specifications and calculate matching scores automatically, eliminating the need for manual technical personnel while maintaining high matching accuracy through sophisticated algorithms.
Solution Approach 2:
The system enables self-service matching by automatically processing technical specifications and generating match results without human intervention. The automated feature extraction and scoring mechanisms allow the system to serve itself in identifying suitable products, freeing up technical personnel for more complex tasks.
2Loss of information
If comprehensive technical feature extraction is performed across multiple sources, then matching completeness is improved, but system complexity increases
Solution Approach 1:
The patent segments the complex task of matching into distinct components: feature extraction, feature representation, and matching score calculation. By dividing the process into modular stages with specialized models for each function, the system achieves comprehensive feature extraction while managing complexity through structured organization of processing steps.
Solution Approach 2:
The patent introduces intermediate representations (feature vectors and embeddings) that mediate between raw technical specifications and final matching scores. These intermediate structures serve as standardized interfaces that simplify the integration of information from multiple diverse sources while maintaining comprehensive feature capture.
3Measurement precision
If detailed technical feature analysis is performed, then matching precision is improved, but computational resources increase
Solution Approach 1:
The patent applies partial action by focusing computational resources on the most discriminative technical features rather than processing all features equally. The system identifies and prioritizes key features that have the greatest impact on matching accuracy, performing detailed analysis only where necessary while using simpler processing for less critical features.
Data Source
AI summary
Systems and methods are provided for detail matching. The method includes training a feature classifier to identify technical features, and training a neural network model for a trained importance calculator to calculate an importance value for each identified technical feature. The method further includes receiving a specification sheet including a plurality of technical features, and receiving a plurality of descriptive sheets each including a plurality of technical features. The method further includes identifying the technical features in the specification sheet and the plurality of descriptive sheets using the trained feature classifier, and calculating an importance for each identified technical feature using the trained feature importance calculator. The method further includes calculating a matching score between the identified technical features of the specification sheet and the identified technical features of the plurality of descriptive sheets based on the importance of each identified technical feature.