Automated Document Segmentation and Coordinate Extraction
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Solution Overview
Problem
Existing methods for managing large documents, such as those used by universities or corporations, require manual extraction and creation of individual documents, leading to inefficiencies and high costs, especially when dealing with thousands of records, and are limited in handling image or scanned documents.
Innovation Solution
A method and apparatus that automate the extraction of information from a large document by identifying extraction attributes, applying coordinates, and creating new documents based on predefined areas, allowing for efficient generation and sharing of personalized documents via email links, with optional password protection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual extraction and creation of individual documents is used, then document personalization is achieved, but time consumption and labor costs increase significantly
Solution Approach 1:
The system segments a large master document into multiple individual documents by automatically extracting records based on unique identifiers. The document is divided into page segments, and information is extracted from specific coordinate areas on each page to create personalized documents for different users, eliminating manual extraction while maintaining customization.
Solution Approach 2:
The system automatically extracts specific information from the large document using coordinate-based positioning and pattern recognition. By identifying unique identifiers and extracting data from predefined coordinate areas, the system creates individual documents without manual intervention, resolving the contradiction between personalization and time consumption.
2Adaptability or versatility
If manual extraction and creation of individual documents is used, then document personalization is achieved, but labor costs and operational complexity increase
Solution Approach 1:
The system performs self-service by automatically processing the document segmentation and information extraction without human intervention. The automated coordinate-based extraction and pattern recognition enable the system to generate personalized documents independently, reducing both labor costs and operational complexity while maintaining document personalization capabilities.
3Productivity
If automatic coordinate-based extraction is implemented, then processing speed increases, but support for image and scanned documents is limited
Solution Approach 1:
The system achieves multi-functionality by supporting multiple document formats including native digital documents, image-based documents, and scanned documents. The coordinate-based extraction method is format-agnostic, allowing the same processing approach to work across different document types, thus maintaining high processing speed while expanding document format support.
4Measurement precision
If information is extracted from predefined coordinate areas, then extraction precision is improved, but flexibility in handling different document layouts is reduced
Solution Approach 1:
The system applies dynamic coordinate positioning that can adapt to different document layouts while maintaining extraction precision. By using pattern recognition to identify unique identifiers and dynamically adjusting coordinate areas based on the specific document structure, the system achieves both precise extraction and layout flexibility, resolving the contradiction between precision and adaptability.
Data Source
AI summary
Electronic documents may be large and have numerous pages, sections and areas of information that are useful to some individuals and not others. It is common for large documents to include some information that is intended for only certain recipients and other information that is intended for other recipients. One example may provide receiving a document that has a number of pages, identifying an extraction attribute, querying the document for the extraction attribute, applying a coordinate to information associated with the extraction attribute, extracting information based on the extraction attribute and a predefined area associated with the at least one coordinate, and creating a new document including the information extracted.