Automated Report Generation from Unstructured Data via OCR
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Solution Overview
Problem
Existing data analysis systems face challenges in efficiently managing and validating large volumes of data, particularly for VAT refunds, due to the impracticality of manual review, human error, and incompatibility with unstructured or semi-structured data formats, leading to inaccurate results and increased costs.
Innovation Solution
A method and system for automatically generating reports by creating structured data templates from partially unstructured data, using optical character recognition and image processing to identify key fields and values, and generating reports based on reporting requirements, thereby reducing computational resources and human error.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual review and validation of data is performed, then data accuracy can be ensured, but the process becomes impractical and time-consuming for large volumes of data
Solution Approach 1:
The patent replaces manual mechanical review processes with automated optical character recognition (OCR) and image processing systems. The OCR technology converts images of documents into machine-readable text, allowing automated validation without human intervention while maintaining accuracy through algorithmic processing of large data volumes.
Solution Approach 2:
The patent introduces an intermediary automated processing layer between the physical documents and the validation system. This intermediary system uses OCR to extract data from images, transforms it into structured formats, and prepares it for validation, thereby enabling efficient processing while preserving data accuracy through systematic transformation.
2Measurement precision
If existing validation solutions require structured data or specific format requirements, then validation accuracy improves, but the system cannot handle unstructured or semi-structured data
Solution Approach 1:
The patent changes the parameter of data structure by using OCR to transform unstructured image data into structured text data. This parameter transformation allows the system to accept diverse input formats (images, scans, photographs) and convert them into a standardized structured format suitable for validation, thereby improving both accuracy and adaptability.
Solution Approach 2:
The patent creates a digital copy of the physical document through OCR technology. The OCR process generates a text-based replica of the image data, which can then be processed and validated using structured data methods. This copying approach allows the system to handle unstructured images while maintaining validation accuracy through the structured text representation.
3Loss of information
If image-based electronic documents are used to contain validation information, then data completeness is maintained, but storage requirements and computational resources increase
Solution Approach 1:
The patent creates a text-based copy of the image data through OCR processing. Instead of storing and processing the entire image file, the system extracts and stores only the essential text information in a compact structured format. This copying approach maintains data completeness for validation purposes while significantly reducing storage requirements compared to retaining original images.
Solution Approach 2:
The patent extracts only the necessary text information from the image documents using OCR technology. Rather than storing complete images, the system extracts and retains only the data fields required for validation (such as transaction amounts, dates, vendor information), thereby maintaining data completeness for validation while minimizing storage requirements by eliminating redundant image data.
Data Source
AI summary
A system and method for automatically generating reports. The method includes: creating at least one template of structured data based on at least a partially unstructured data, wherein the partially unstructured data is obtained based on at least one reporting requirement; identifying, based on the at least partially unstructured data, at least one key field and at least one value; creating, based on the at least partially unstructured data, a dataset including the at least one key field and the at least one value; and generating a report based on the at least one created template and the at least one reporting requirement.