Document Data Extraction Using Fingerprint-Guided Feedback
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Solution Overview
Problem
Existing data extraction systems from documents face ambiguities due to varying document formats, content complexity, and image quality, necessitating significant user intervention for validation.
Innovation Solution
Implementing a system that uses document fingerprints to identify suitable feedback files for automated data extraction enhancement, allowing for automated feedback-based modification of extracted data, reducing the need for user participation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated data extraction is performed without user guidance, then processing speed increases, but data extraction accuracy deteriorates due to ambiguities in document formats and content
Solution Approach 1:
The system performs preliminary actions by creating document fingerprints and storing validation guidance in feedback files before actual data extraction occurs. When processing new documents, the system retrieves previously validated extraction patterns and applies them automatically, resolving ambiguities without requiring real-time user intervention. This preliminary preparation enables both high speed and high accuracy simultaneously.
Solution Approach 2:
The system implements feedback mechanisms by storing user validation results in feedback files associated with document fingerprints. These feedback files contain guidance on how to correctly extract data from specific document formats. The system continuously retrieves and applies this feedback information during automated extraction, improving accuracy while maintaining productivity through learned patterns from previous validations.
2Measurement precision
If user validation is performed on extracted data, then data extraction accuracy improves, but time consumption increases
Solution Approach 1:
User validation is performed preliminarily on representative documents to create feedback files with extraction guidance. Once these feedback files are established, subsequent extractions automatically apply the validated patterns without requiring repeated user validation. This shifts the time investment to an initial setup phase, enabling rapid automated processing thereafter while maintaining high accuracy through pre-validated extraction rules.
Solution Approach 2:
The system enables self-service by using stored feedback files to automatically validate and correct extracted data without requiring continuous user involvement. The feedback files contain guidance that allows the system to self-correct extraction errors and validate data accuracy autonomously, significantly reducing time consumption compared to manual validation while maintaining high extraction accuracy.
3Extent of automation
If feedback files are created and stored for document validation, then automation capability improves, but system complexity increases
Solution Approach 1:
The system uses document fingerprints as simplified copies or representations of complex document structures. Instead of storing and processing entire documents or their full complexity, the system creates compact fingerprint identifiers that capture essential document characteristics. These fingerprints serve as keys to retrieve appropriate feedback files, enabling automation while managing complexity through this copying approach.
Solution Approach 2:
The system segments the validation process by creating separate feedback files for different document types and formats, each associated with specific fingerprints. This segmentation allows the system to handle complexity in a modular way, where each feedback file contains guidance for specific document patterns. The segmentation enables targeted automation without requiring a single complex validation system to handle all document variations.
Data Source
AI summary
Improved techniques for extraction of data from documents, namely, from images of documents, so as to better enable software automation. The software automation can, for example, be provided by software robots of RPA systems. The improved techniques can provide automated feedback-based modification of data extracted from an image of a document through use of previously used validation guidance provided by a user in validating extracted data from a same or similar document. In one embodiment, the automated feedback-based modification can locate an appropriate feedback file through use of document fingerprints and document clusters. Then, guidance from the appropriate feedback file can be used to automatically modify at least a portion of the data extracted data from the image based on the guidance retrieved from the feedback file. Advantageously, the improved techniques can reduce the need for user participation in validation of data extracted from images of documents, and yield greater and more accurate automated data extraction.