AI Entry Field Identification for Electronic Document Templates
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Solution Overview
Problem
Existing technologies fail to accurately identify and determine the positions, sizes, and types of entry fields in electronic documents, which are essential for creating electronic document templates for systems like electronic signatures or contracts.
Innovation Solution
An apparatus and method using AI to extract feature information from original electronic documents, including probability information and pre-trained deep learning models, to identify entry fields and generate templates with identified positions, sizes, and types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual review and determination of entry fields is performed by the user, then accuracy of entry field identification can be maintained, but time consumption and labor intensity increase significantly
Solution Approach 1:
The patent replaces the manual mechanical review process with an automated AI-based system that uses deep learning models to extract feature information from electronic documents and identify entry fields automatically, eliminating the need for manual user review while maintaining high accuracy
Solution Approach 2:
The system enables electronic documents to self-identify their entry fields through automated AI processing, where the document processing system automatically extracts feature information and determines entry field positions, sizes, and types without requiring user intervention
2Productivity
If automated methods are used to extract feature information from electronic documents, then productivity increases, but measurement precision of entry field identification may deteriorate
Solution Approach 1:
The system performs preliminary extraction of feature information from electronic documents using deep learning models before final entry field identification, preparing structured data that improves the accuracy of subsequent automated processing while maintaining high productivity
Solution Approach 2:
The AI-based system uses feedback mechanisms where extracted feature information is continuously refined and used to improve entry field identification accuracy, allowing the system to learn from processed documents and maintain high precision while operating automatically
3Adaptability or versatility
If comprehensive feature information is extracted from all document types, then adaptability improves, but device complexity increases
Solution Approach 1:
The patent implements a universal deep learning-based feature extraction system that can process multiple document types (images, PDFs, Office files) through a single unified architecture, achieving high adaptability without proportionally increasing system complexity through modular design
Data Source
AI summary
An apparatus for identifying entry fields in electronic documents based on artificial intelligence and a method for identifying entry fields in electronic documents using the same are provided. The apparatus for identifying entry fields in electronic documents based on artificial intelligence includes an input unit that acquires an original electronic document in which entry field information including type information and position information is not identified, a feature extraction unit that extracts feature information for deriving the entry field information from the original electronic document in consideration of the data type of the original electronic document, and a field classification unit that identifies the entry field information from the feature information.