Intelligent Document Processing Assistant for Data Extraction
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Solution Overview
Problem
Intelligent document processing (IDP) systems face challenges in widespread adoption due to the need for skilled IT resources and user intimidation with current data entry systems, limiting only a few skilled individuals within a company to perform these tasks.
Innovation Solution
A user-friendly apparatus that automatically analyzes electronic documents to determine their type, extracts relevant text data, and presents field names and values on a screen for user confirmation and modification, allowing for efficient data extraction and transmission to a target data storage service.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated machine learning modules are used for document processing, then productivity is improved, but device complexity increases requiring skilled IT resources
Solution Approach 1:
The patent introduces an intermediary training system that mediates between the complex machine learning modules and end users. This training system processes documents and allows users to provide corrections without requiring users to understand the underlying machine learning complexity, thus maintaining high productivity while shielding users from device complexity
Solution Approach 2:
The system enables self-service by allowing users to directly interact with and correct extracted data without needing skilled IT resources. Users can independently train the system by providing corrections, eliminating the need for specialized technical knowledge to operate the machine learning modules
2Measurement precision
If skilled IT resources are required to operate machine learning modules, then measurement precision is improved, but ease of operation deteriorates
Solution Approach 1:
The training system enables any user to improve data extraction accuracy through simple corrections without requiring skilled IT resources. Users can independently interact with extracted data, provide corrections, and retrain the system, making precise data extraction accessible to all users regardless of technical expertise
Solution Approach 2:
The system implements feedback mechanisms where user corrections are used to retrain and improve the machine learning models. This continuous feedback loop allows users to enhance measurement precision through simple interactions rather than requiring deep technical knowledge of the underlying algorithms
3Manufacturing precision
If current data entry systems are used, then manufacturing precision is maintained, but ease of operation deteriorates making users intimidated
Solution Approach 1:
Instead of requiring users to manually enter data into complex systems, the patent inverts the approach by having the system automatically extract data and present it for user confirmation. Users review and correct extracted data in a simplified interface rather than navigating complex data entry systems, maintaining precision while dramatically improving ease of operation
Data Source
AI summary
Techniques for an intelligent document processing assistant are provided. In one technique, an electronic document is received and content thereof is automatically analyzed to determine a document type of the electronic document. Based on the document type, text data is extracted from the electronic document. The text data comprises multiple field values that correspond to multiple field names that are associated with the document type. Some of the field names and field values are presented on a screen of a computing device. In response to receiving, through the computing device, first user input that modifies at least one data item (in the text data that was extracted from the electronic document), the text data is updated to generate modified text data. Second user input that confirms the modified text data is received through the computing device. The modified text data is transmitted over a network to a data storage service.