Text Processing Apparatus for Accurate Segment Identification
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Solution Overview
Problem
Existing text alignment techniques fail to correctly determine portions in a first text that should be described in a second text when information is absent in the second text, leading to incorrect identification of segments that should be written.
Innovation Solution
A text processing apparatus and method that contrasts a first text set with a second text set generated through different processes, using a segment determination unit to identify homogeneous segments and a descriptive content determination unit to assess whether each segment in the first text should be described in the corresponding second text, even when information is absent.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing text alignment techniques are used to determine portions in a first text that should be described in a second text, then the alignment process can be completed, but the determination becomes incorrect when information is absent in the second text
Solution Approach 1:
The patent segments the first text into multiple candidate segments and individually evaluates each segment's importance and describability. This segmentation allows the system to handle missing information in the second text by assessing each segment independently rather than requiring complete information across the entire text.
Solution Approach 2:
The patent performs preliminary actions by first determining the importance of each candidate segment before assessing whether it should be described in the second text. This preliminary importance assessment allows the system to identify critical information that should be preserved even when the second text has missing information.
2Adaptability or versatility
If traditional alignment techniques are applied, then text comparison can be performed, but the complexity increases when handling texts generated through different generation processes
Solution Approach 1:
The patent changes the parameters of text evaluation by introducing multiple dimensions including importance determination and describability assessment. Instead of using a single alignment metric, the system evaluates segments based on multiple parameters that adapt to different text generation processes, thereby handling diversity without excessive complexity.
Solution Approach 2:
The patent introduces an intermediary evaluation layer that assesses candidate segments based on their importance and describability before final alignment. This intermediary step acts as a mediator between the first and second texts, simplifying the alignment process by pre-filtering and prioritizing segments that need to be matched.
3Measurement precision
If comprehensive text analysis is performed to identify all portions that should be described, then accuracy improves, but the time required for analysis increases
Solution Approach 1:
The patent applies partial action by focusing analysis on candidate segments that are most likely to be important, rather than uniformly analyzing every portion of the text. The system generates candidate segments and selectively evaluates them based on their characteristics, achieving high accuracy without the time cost of comprehensive analysis of all text portions.
Solution Approach 2:
The patent applies local quality by determining importance and describability for each candidate segment individually rather than applying a uniform analysis across the entire text. This localized evaluation allows the system to concentrate computational resources on segments that require detailed analysis while using simpler criteria for other segments.
Data Source
AI summary
A text processing apparatus is provided with a segment determination unit 36 and a descriptive content determination unit 33. The segment determination unit 36 determines, with respect to a homogeneous segment that is similar to segments constituting a first text which is set as an analysis target (analysis target text) and that is included in another first text, whether the content thereof is included in a second text. The descriptive content determination unit 33 determines whether each segment constituting the analysis target text should be described in a corresponding second text, based on the determination result.