Automated Document Extraction and Segmentation for Private Records
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Solution Overview
Problem
Existing methods for managing large documents, such as PDF files containing information for multiple individuals, require manual extraction and creation of individual documents, which is time-consuming and inefficient, 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 process of extracting information from a large document based on predefined attributes and coordinates, creating new documents for each individual, and sharing these documents via email links, allowing for efficient management and access of information without the need for manual handling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual extraction and creation of individual documents is used, then document management can be performed, but the process is time-consuming and inefficient
Solution Approach 1:
The system automatically extracts information from large documents and creates individual documents without human intervention. The automated extraction process identifies relevant information based on predefined criteria and generates separate documents for each recipient, eliminating the need for manual document processing while maintaining high accuracy and efficiency.
2Quantity of substance
If large documents with many pages are created to store multiple records, then all information can be stored in one file, but the file size becomes large and difficult to manage
Solution Approach 1:
The system automatically divides a large master document containing multiple records into separate individual documents based on extracted identification information. Each recipient receives only their relevant document, transforming one complex large-file management problem into multiple simple small-file management tasks, thereby reducing overall system complexity while preserving all information.
3Extent of automation
If automated extraction is implemented, then processing time is reduced, but the system must handle image-based or scanned documents which is limited in conventional applications
Solution Approach 1:
The system is designed to extract information from multiple document types including native digital formats and image-based or scanned documents. By incorporating universal extraction capabilities that work across different document formats and types, the system maintains high automation levels while expanding adaptability to handle diverse document sources that conventional applications cannot process.
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 including a number of pages, identifying a number of extraction attributes corresponding to various users identified in the document, querying the document for the extraction attributes, and creating a number of new documents corresponding to the extraction attributes.