Document Verification Service Using Classification-Based Template Extraction
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Solution Overview
Problem
Organizations face challenges in accurately and efficiently extracting and verifying data from electronic documents due to variations in document structure and content, leading to incorrect classification and increased resource usage.
Innovation Solution
The implementation of a document verification service that uses multiple classification models to templatize documents based on type and source, allowing for the extraction and verification of target data using generated templates, which are calibrated to account for structural variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple classification models and templates are used to accurately classify and extract data from documents with varying structures, then data extraction accuracy improves, but system complexity increases
Solution Approach 1:
The system segments the document processing task into multiple classification models (document type classification, source classification) and template-based extraction. Each model handles a specific aspect of document variation, allowing accurate processing of diverse document structures while maintaining manageable system complexity through modular design.
Solution Approach 2:
The system dynamically selects and applies appropriate templates based on document type and source classification results. This dynamic adaptation allows the system to handle varying document structures efficiently without requiring a static, overly complex system design that attempts to accommodate all variations simultaneously.
2Reliability
If manual verification methods are used for documents with structural variations, then verification accuracy can be maintained, but processing time and resource usage increase
Solution Approach 1:
The system performs automated document verification by extracting data using classification-based template selection and comparing extracted data against expected values or additional document sections. This self-service capability maintains verification accuracy while eliminating manual processing requirements, thereby reducing processing time and resource consumption.
3Productivity
If generic extraction methods are applied to all documents, then processing speed is maintained, but extraction accuracy decreases due to document structure variations
Solution Approach 1:
The system performs preliminary classification of document type and source before applying extraction templates. This preliminary action enables the selection of appropriate extraction strategies tailored to each document category, maintaining high extraction accuracy while preserving processing speed through automated, structured workflow.
Data Source
AI summary
In one aspect, an example methodology implementing the disclosed techniques includes, by a document verification service, a reference text combination of a document to verify and determining, using a first classification model, a type of the document based on the reference text combination of the document. The method also includes, by the document verification service, determining, using a second classification model, a source of the document based on the reference text combination of the document, and determining a template for the type of the document and the source of the document, the template indicating positioning of target data in documents of the type and source as the document. The method further includes, by the document verification service, one or more target data from the document using the template and the one or more target data extracted from the document.