Document Information Evaluation Device for Partial Match Retrieval
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Solution Overview
Problem
Existing document information retrieval systems often retrieve literature with low similarity scores when content matching conditions are partially met, leading to inefficient user searches, requiring repeated keyword selection and increased time to find relevant documents.
Innovation Solution
A document information evaluating device and method that decompose input information into constituent units, calculate matching scores, and provide a comparison table showing differences, allowing users to self-evaluate and prioritize results, with the option to fix desired documents for recalculating matching conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If document information is retrieved based on overall similarity scoring, then search completeness is maintained, but search accuracy deteriorates when content matches only partially
Solution Approach 1:
The patent segments document information into multiple constituent units (such as claims, paragraphs, or sections) and calculates matching scores for each segment independently. This allows the system to identify documents where specific segments match the search conditions even if the overall document similarity is low, thereby improving search accuracy for partial matches while maintaining comprehensive retrieval through aggregate scoring.
2Reliability
If literature with low overall similarity is retrieved to ensure completeness, then search coverage is improved, but user time and effort increase due to repeated keyword selection
Solution Approach 1:
By segmenting documents and scoring individual segments, the system can quickly identify and prioritize relevant portions without requiring users to manually adjust keywords multiple times. The comparison table generated from segment-level scoring allows users to efficiently assess relevance at a glance.
Solution Approach 2:
The system provides feedback through a comparison table that displays segment-level matching scores and highlights differences between search conditions and document content. This feedback mechanism enables users to quickly evaluate retrieved documents and determine whether further keyword adjustment is necessary, reducing iterative search cycles.
3Measurement precision
If segment-level similarity scoring is implemented to improve accuracy, then retrieval precision is improved, but system complexity increases
Solution Approach 1:
The patent divides the document processing task into manageable segments, calculating matching scores for each segment independently. This segmentation approach simplifies the overall complexity by breaking down the complex task of full-document comparison into smaller, more manageable unit comparisons that can be processed systematically.
Solution Approach 2:
The segment-level scoring system serves multiple functions simultaneously: it improves retrieval precision by identifying partial matches, generates informative comparison tables for user evaluation, and provides a framework for both initial retrieval and iterative search refinement. This multi-functionality reduces the need for separate systems for different search scenarios.
4Measurement precision
If comprehensive document comparison is performed to ensure accuracy, then evaluation thoroughness is improved, but processing speed deteriorates
Solution Approach 1:
By segmenting documents into constituent units and comparing segments independently, the system can process and evaluate document relevance more quickly than performing comprehensive full-document comparisons. The segment-level approach allows for faster initial filtering and identification of potentially relevant documents.
Solution Approach 2:
The system performs preliminary segment-level comparison and generates a comparison table before requiring user evaluation. This preliminary action identifies obviously relevant or irrelevant segments, allowing the system to prioritize processing and reduce the time needed for thorough evaluation of all document portions.
Data Source
AI summary
An information acquiring unit configured to acquire input information input from a user terminal that is able to be operated by a user from the user terminal, a storage unit configured to store a plurality of pieces of document information, a calculation unit configured to decompose the input information into predetermined constituent units and calculate a matching condition with one piece of document information among the plurality of pieces of document information stored in the storage unit as a score for each decomposed constituent unit, an output unit configured to output a comparison table representing a degree of difference between the input information and the document information for each constituent unit on the basis of the score, and an input unit configured to input a self-evaluation of the document information that is performed by the user to the comparison table are included.