Form Extractor for Resilient Document Data Extraction
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Solution Overview
Problem
Manual data extraction from documents is repetitive and time-consuming, especially when dealing with similar documents, and existing tools require complex configurations using various algorithm techniques like machine learning and rule-based methods, which are not resilient to document variations such as position changes, rotation, and format differences.
Innovation Solution
A form data extractor for document processing using Robotic Process Automation (RPA) workflows that includes user-configurable templates for identifying document types and extracting data, capable of adapting to variations in document position, rotation, size, skew, and file formats, allowing for efficient data extraction across different document types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual data extraction is performed, then data can be extracted from documents, but it is repetitive and time-consuming
Solution Approach 1:
The system performs self-service by automatically extracting data from documents using configured templates and algorithms without requiring manual human intervention for each extraction task, thereby improving productivity and eliminating repetitive manual work
Solution Approach 2:
The patent replaces the mechanical manual process of data extraction with an automated computational system using machine learning algorithms and template-based processing, substituting human manual labor with automated technological processes
2Reliability
If existing extraction tools are configured using machine learning and rule-based methods, then data extraction capability is improved, but the configuration becomes complex
Solution Approach 1:
The system segments the complex extraction task into manageable components using configurable templates that define specific fields and their locations, allowing users to configure extraction by breaking down documents into discrete extractable elements rather than configuring entire extraction processes
Solution Approach 2:
The patent introduces templates as an intermediary layer between the user and the complex machine learning algorithms, allowing users to configure extraction through simple template definitions while the system handles the complex algorithmic processing in the background
3Extent of automation
If rule-based configurations are used for data extraction, then extraction can be automated, but the system is not resilient to document variations such as position changes, rotation, and format differences
Solution Approach 1:
The system implements dynamic extraction by using machine learning algorithms that can adapt to variations in document position, rotation, and format, allowing the extraction process to dynamically adjust to different document states rather than relying on fixed static rules
Solution Approach 2:
The patent employs parameter changes by training machine learning models to recognize and extract data based on various document parameters including position, orientation, and format variations, allowing the system to maintain automation while adapting to different document configurations
Data Source
AI summary
The present system and method relate generally to the field of Robotic Process Automation, particularly to a form data extractor for document processing. The system and method relate to a form extractor for document processing using RPA workflows that can be easily configured for different document types. The form extractor includes a set of templates for identifying the document type (classification) and extracting data from the documents. The templates can be configured, i.e., by the user, by defining the fields to be extracted and the position of the field on the document. The form extractor is resilient to changes in the position of the template on a page, as well as to scan rotation, size, quality, skew angle variations and file formats, thus allowing RPA processes to extract data from documents that need ingestion, independent of how they are created.