Automated Document Analysis for Multilingual Patent Claims
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Solution Overview
Problem
The rapid increase in document information across industries like law, education, and journalism makes manual document analysis impractical due to high costs and inconsistencies, especially when dealing with multiple languages, as it requires large numbers of humans and introduces subjective errors.
Innovation Solution
An automated system that analyzes documents by filtering, pre-processing, and calculating the breadth of document portions, using techniques such as stop word removal, stemming, and anomaly detection, to provide a human-emulative analysis capable of handling documents in various languages and jurisdictions, with a user interface for displaying results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual human analysis is used to analyze documents in multiple languages, then analysis accuracy can be maintained through human judgment, but the cost increases and throughput decreases significantly
Solution Approach 1:
The patent uses machine translation to create translated versions of source documents, allowing automated analysis systems to process multiple languages without requiring human translators for each document. This copying approach maintains consistency while enabling high-volume processing across languages.
Solution Approach 2:
The system changes the language parameter by translating documents into a target language, allowing the automated analysis system to process documents in its native language. This parameter transformation enables the system to maintain high throughput while analyzing multilingual document sets.
2Productivity
If multiple different people are hired to analyze documents to increase throughput, then more documents can be processed, but inconsistencies are introduced due to variation in subjective judgment
Solution Approach 1:
The automated analysis system provides universal processing capabilities across all documents regardless of language or subject matter. A single system performs the analysis function consistently for all inputs, eliminating the variability introduced by multiple human analysts while maintaining high throughput.
Solution Approach 2:
The system uses automated translation and analysis that operates independently without human intervention for each document. This self-service capability ensures consistent application of analysis criteria while processing large volumes of documents through algorithmic rather than human judgment.
3Measurement precision
If human analysts are used to analyze documents in different languages, then language-specific nuances can be captured, but the cost and time requirements increase dramatically
Solution Approach 1:
The system creates translated copies of source documents in the target language, allowing automated analysis to capture language nuances through machine translation. This approach preserves the essence of the original language content while enabling rapid automated processing without requiring human analysts fluent in each source language.
Solution Approach 2:
The system performs translation as a preliminary step before analysis, converting all documents to the target language in advance. This preliminary action allows the main analysis process to proceed efficiently with standardized language input, reducing the time required for analysis while maintaining capability to handle language-specific content.
4Productivity
If automated document analysis is implemented to increase throughput, then processing speed and cost efficiency improve, but the ability to handle varying languages and jurisdictions becomes more complex
Solution Approach 1:
The automated system is designed with universal translation and analysis capabilities that handle multiple languages and jurisdictions through a single integrated platform. This multi-functionality allows the system to process diverse document types and languages without requiring separate specialized systems, managing complexity while maintaining high processing speed.
Solution Approach 2:
The system uses machine translation as an intermediary step that converts documents from various languages into a common target language. This intermediary process simplifies the subsequent analysis by standardizing input language, reducing the complexity of handling multiple languages directly while preserving the ability to process international documents.
Data Source
AI summary
Manual human processing of documents often generates results that are subjective and include human-error. The cost and relatively slow speed of manual, human analysis makes it effectively impossible or impracticable to perform document analysis at the scale, speed, and cost desired in many industries. Accordingly, it may be advantageous to employ objective, accurate rule-based techniques to evaluate and process documents. This application discloses data processing equipment and methods specially adapted for a specific application: analysis of the breadth of documents. The processing may include context-dependent pre-processing of documents and sub-portions of the documents. The sub-portions may be analyzed based on word count and commonality of words in the respective sub-portions. The equipment and methods disclosed herein improve upon other automated techniques to provide document processing by achieving a result that quantitatively improves upon manual, human processing.