Document Delta Generation with Non-Meaningful Change Filtering
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Solution Overview
Problem
Current methods for updating tax and compliance form knowledge bases are manual, time-consuming, costly, and prone to false positives due to their inability to accurately identify substantive changes between consecutive years of documents.
Innovation Solution
A system that compares documents in machine-readable format to automatically generate deltas, filtering out non-substantive changes and providing only substantive changes in a structured format, using a delta generation module and similarity scoring to identify meaningful textual differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual methods using PDF Comparer tools are used to identify changes between documents, then changes can be detected visually, but the process is slow, costly, and yields many false positives
Solution Approach 1:
The patent replaces manual visual comparison methods with an automated computer-based system that uses optical character recognition (OCR) and text analysis algorithms to detect and classify changes between document versions, eliminating human labor while improving accuracy through systematic processing
Solution Approach 2:
The system automatically performs document comparison, change detection, and classification without human intervention. The computer-based system processes documents independently, applying predefined rules and algorithms to identify substantive changes versus trivial changes, thereby achieving both high productivity and accurate measurement
2Reliability
If manual updating methods are used for tax content knowledge bases, then changes can be identified, but the process is tedious and time-consuming
Solution Approach 1:
The patent substitutes manual updating processes with an automated computer system that uses OCR technology and text analysis to reliably identify changes between document versions. The system processes documents automatically, applying consistent criteria for detecting substantive changes, thereby eliminating the time-consuming nature of manual updates while maintaining or improving reliability
Solution Approach 2:
The system enables continuous automated processing of document updates without interruption or manual intervention. By implementing an ongoing automated comparison and classification process, the system eliminates the intermittent, tedious nature of manual updates and achieves continuous reliable operation
3Difficulty of detecting and measuring
If current PDF comparison tools are used, then visual changes can be detected, but substantive content changes cannot be distinguished from trivial changes
Solution Approach 1:
The patent replaces simple visual comparison tools with an advanced computer-based system that uses OCR to convert images to text, then applies natural language processing and classification algorithms to distinguish substantive content changes from trivial formatting changes, thereby recovering lost information about the nature of changes
Solution Approach 2:
The system introduces an intermediary text analysis layer between visual document comparison and change detection. By converting documents to text format and applying linguistic analysis, the system mediates between raw visual data and meaningful change identification, enabling distinction between substantive and trivial changes that visual tools cannot detect
Data Source
AI summary
Generating a difference between a first and second plurality of lines of text in structured machine-readable format may include determining, by at least one processor, a line of the second plurality of lines that constitutes a best match for a line of the first plurality of lines. The line of the first plurality of lines and its respective best match may be associated with a similarity score. The at least one processor may compare the similarity score to a threshold value. In response to determining that the similarity score is greater than or equal to the threshold value, the at least one processor may compute, the textual difference between the line of the first plurality of lines and its best match. In response to computing the textual difference, the at least one processor may analyze the textual difference to identify a non-meaningful change. In response to identifying a non-meaningful change, the at least one processor may record the textual difference in a delta with a flag indicating the presence of the non-meaningful change.