Legal Document Deviation Detection Through Two-Level Text Analysis
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Solution Overview
Problem
Manual deviation detection in legal documents is time-consuming and often leads to inconsistent results, necessitating a need for automated systems to improve efficiency and accuracy.
Innovation Solution
A system and method for detecting deviations between documents through first and second level analyses, including long string matching, textual similarity mapping, tokenization, and semantic analysis to identify identical, similar, deleted, and added text groupings, with visual comparison results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual deviation detection is performed by legal practitioners, then the process can be completed with simple tools, but it is very time-consuming and leads to inconsistent results
Solution Approach 1:
The patent replaces the manual mechanical review process with an automated computational system that uses natural language processing, machine learning models, and text analysis algorithms to detect deviations between legal documents, thereby eliminating time-consuming manual comparison while maintaining or improving detection accuracy
Solution Approach 2:
The system enables self-service deviation detection by automatically analyzing legal documents without requiring practitioner intervention for each comparison, allowing the system to perform its own analysis and generate deviation reports autonomously
2Productivity
If automated deviation detection systems are implemented, then efficiency and consistency are improved, but system complexity increases
Solution Approach 1:
The patent segments the deviation detection process into distinct modular components including text preprocessing modules, similarity analysis modules, deviation identification modules, and reporting modules, allowing each component to be developed and maintained independently while working together to achieve high productivity
Solution Approach 2:
The system is designed as a universal platform that can handle multiple types of legal documents and deviation detection scenarios through configurable parameters and adaptable algorithms, enabling one system to perform multiple functions without proportionally increasing complexity
Data Source
AI summary
The present disclosure is directed towards systems and methods for detecting deviations from a standard document in a document being analyzed. The inventive systems and methods include performing a first level analysis to detect portions of a standard that are identical to, similar to, deleted from, and added to a document being evaluated. A second level analysis may be applied to those portions of the standard that are similar, but not identical to, portions of the document being evaluated to assist a user in identifying similarities and differences between the two portions of text.