Federated Text Coherency Analysis for Confidential Document Comparison
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Solution Overview
Problem
Conventional document management systems lack a convenient mechanism for objective and subjective comparison of documents, making it difficult for organizations to understand the strengths and weaknesses of legal documents like termination clauses relative to industry standards and potential risks, which is a costly and time-consuming endeavor.
Innovation Solution
A federated system and method for analyzing language coherency and anomaly detection that converts text portions into tensors, compares them across multiple computing environments using local coherency systems, and aggregates similarity and risk scores without accessing the underlying documents, leveraging a larger corpus for analysis while maintaining confidentiality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional document management systems are used for document comparison, then document organization and modification tools are provided, but objective and subjective comparison of different documents is not available
Solution Approach 1:
The patent introduces an intermediary comparison mechanism that bridges the gap between documents. This intermediary system enables objective and subjective comparison by creating a unified comparison space where documents can be evaluated against each other and against industry standards without requiring complex manual analysis processes.
Solution Approach 2:
The system provides universal comparison capabilities that work across different document types and sources. The comparison mechanism is designed to handle multiple functions including objective textual comparison, subjective evaluation against industry standards, and risk assessment, all within a single integrated platform.
2Measurement precision
If manual legal review is performed to analyze document accuracy and risk, then comprehensive analysis is achieved, but significant time and cost are required
Solution Approach 1:
The system enables self-service document analysis by automatically evaluating document accuracy, strength, and risk against industry standards. The automated comparison mechanism performs comprehensive legal review tasks independently, eliminating the need for manual lawyer intervention while maintaining high analysis accuracy.
Solution Approach 2:
The patent replaces manual mechanical review processes with automated electronic comparison systems. The system uses computational methods to substitute for human legal analysis, achieving comprehensive document review capabilities through algorithmic processing rather than manual examination.
3Loss of information
If documents are accessed and analyzed to understand their strengths and weaknesses, then comprehensive insights are obtained, but document confidentiality and security are compromised
Solution Approach 1:
The system extracts only the necessary comparison information from documents without accessing or exposing the full document content. By extracting and comparing only the essential features needed for analysis, the system provides comprehensive insights while maintaining document confidentiality and preventing unauthorized exposure of sensitive information.
Solution Approach 2:
An intermediary analysis layer is introduced between the documents and the user interface. This intermediary system processes documents through secure comparison mechanisms and presents only the necessary insights, acting as a buffer that protects document confidentiality while still enabling comprehensive analysis.
4Adaptability or versatility
If a large corpus of documents is used for comparison, then broader industry standard understanding is achieved, but system complexity and data management difficulty increase
Solution Approach 1:
The system segments the large document corpus into manageable categories and groups based on document type, industry standard, and relevance. This segmentation allows the system to handle broad corpus coverage efficiently by processing documents in organized segments rather than as a monolithic collection, reducing overall system complexity.
Solution Approach 2:
The system employs universal comparison algorithms and data structures that can handle diverse document types and sources uniformly. This universal approach enables broad corpus coverage without requiring separate processing mechanisms for each document category, simplifying system architecture while maintaining versatility.
Data Source
AI summary
Aspects of the present disclosure involve systems and methods for evaluating a piece of text or document against many corpuses of text or documents located on sources which may be the same and/or different from the text of interest in a tensorized manner and aggregating the coherence/anomaly score against some or all of the entire corpus. This joining of multiple data sources for evaluating the given piece or text may be a “federated” system as disparate data sources, each of which may contain confidential or otherwise private information, may be considered as a single repository of texts or documents. The systems and methods provide for a coherency and/or anomaly check of a piece of text of a document against similar pieces of text to determine a similarity of the piece of text to a large corpus of documents stored in disparate locations.