Structured Data Template Matching for Variable File Layouts
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Solution Overview
Problem
Existing systems struggle with efficiently extracting structured data from files with varying layouts and formats, leading to manual inspection and labor-intensive data normalization, especially in large organizations dealing with multiple suppliers and customers.
Innovation Solution
A method and system utilizing image classification models to analyze visual representations of structured data files, compare featuresets using cosine distance, and automatically generate templates for key-value pair extraction, allowing for standardized data formats across varying file structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection is used to extract information from structured data files, then accuracy can be maintained, but time consumption and cost increase significantly
Solution Approach 1:
The patent replaces manual mechanical inspection with an automated image classification system that uses visual representations and feature extraction algorithms to identify and extract data from structured files, eliminating the need for human reviewers to manually scan through documents while maintaining extraction accuracy
Solution Approach 2:
The system creates visual representations (copies) of structured data files and analyzes these representations through image classification models to extract information, allowing the system to process multiple files simultaneously without human intervention and significantly reducing time consumption
2Productivity
If automated extraction methods are implemented, then processing speed increases, but the system becomes more complex
Solution Approach 1:
The patent segments the data extraction process into distinct functional modules: visual representation generation, feature extraction, template matching, and data extraction. This segmentation allows each component to be developed and optimized independently, managing overall system complexity while maintaining high processing speed
Solution Approach 2:
The system introduces visual representations as an intermediary between the raw structured data files and the extraction algorithms. These visual representations serve as a standardized intermediate format that simplifies the extraction process and reduces the complexity of handling diverse file formats directly
3Adaptability or versatility
If the system accommodates variations in file layouts and locations, then adaptability improves, but processing accuracy may decrease
Solution Approach 1:
The patent employs dynamic template matching that can adapt to variations in data location and layout. The system generates visual representations and extracts features that can be matched against multiple template patterns, allowing accurate extraction even when data positions vary across different file formats and layouts
Solution Approach 2:
The system changes the parameters of visual representation generation and feature extraction to accommodate different file layouts. By adjusting these parameters dynamically, the system maintains high extraction accuracy across diverse data formats without requiring manual reconfiguration
Data Source
AI summary
The present application describes methods and systems which may automatically extract structured data. One method includes receiving a structured data file in a first data file structure; generating a visual representation of the structured data file; extracting a featureset including a plurality of features from the visual representation via an image classification model; comparing the featureset of the visual representation to one or more featuresets associated with other structured data files; based on a determination that the featureset is within a predetermined threshold distance from an identified featureset from among the one or more featuresets, selecting a template associated with identified featureset, the template including a definition of at least one key and at least one position; using the selected template to identify key-value pairs within the structured data file; and automatically generating an output file in a common data file structure from information in the structured data file.