Automated Document Analysis Emulating Human Judgment
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Solution Overview
Problem
Current document analysis methods, despite advancements in artificial intelligence, still rely on manual human analysis for tasks requiring subjective judgment, which is costly, slow, and prone to inconsistencies, especially when dealing with large volumes of documents.
Innovation Solution
An automated system that analyzes documents by filtering, preprocessing, and assigning breadth scores based on word count and commonality, emulating human analysis by comparing documents within a corpus to determine relative breadth and generate rankings, while flagging anomalies for manual review.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual human analysis is used for document analysis tasks involving subjective judgment, then analysis quality and accuracy are improved, but cost and time consumption increase significantly
Solution Approach 1:
The system creates a computational model that copies and emulates human analytical processes. By representing human judgment patterns, knowledge, and reasoning methods in a machine-executable format, the system achieves automated document analysis that maintains high analysis quality while eliminating the time consumption and cost associated with manual human analysis.
2Measurement precision
If manual human analysis is used for document analysis, then subjective judgment accuracy is improved, but cost increases making large-scale analysis impracticable
Solution Approach 1:
The system creates a computational model that copies and emulates human analytical processes. By representing human judgment patterns, knowledge, and reasoning methods in a machine-executable format, the system achieves automated document analysis that maintains high analysis quality while eliminating the time consumption and cost associated with manual human analysis.
3Productivity
If multiple different people are used to provide manual analysis, then larger volume of documents can be analyzed, but inconsistencies increase due to variation in subjective judgment
Solution Approach 1:
The system creates a universal analytical model that can process any document within its domain consistently. This single automated system performs the function of multiple human analysts simultaneously, eliminating the variability and inconsistencies that arise when different individuals apply their own subjective judgment criteria to the same or different documents.
4Productivity
If automated document analysis using computers is used, then speed and cost are improved, but analysis quality deteriorates for tasks involving subjective judgment
Solution Approach 1:
The system creates a computational model that copies and emulates human analytical processes. By representing human judgment patterns, knowledge, and reasoning methods in a machine-executable format, the system achieves automated document analysis that maintains high analysis quality while eliminating the time consumption and cost associated with manual human analysis.
Data Source
AI summary
Automatic processing of documents often generates results far different from those obtained by manual human processing. For a given document processing task, many different techniques can be tried but it is often not known which will best emulate manual, human processing. 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 is quantitatively closer to manual, human processing.