Form Feature Segmentation for Context-Aware Text Correction
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Solution Overview
Problem
Existing character string correction systems fail to accurately provide candidate correct expressions tailored to the specific field of form use and attributes of the filling-out person, leading to potential incorrect corrections due to similarity-based matching without considering form features or user attributes.
Innovation Solution
An information processing apparatus that identifies form features and accumulation of correction tendencies for specific form types, displaying candidate correct expressions based on these identified features to ensure accurate corrections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If candidate correct expressions are displayed based only on character string similarity or past correction records without considering form features, then the system operation is simple and fast, but the correction accuracy deteriorates because candidate expressions suitable for the specific form field are not provided
Solution Approach 1:
The patent segments the correction system by form features, dividing correction tendencies into separate accumulations for different form types (e.g., medical forms, financial forms). This allows the system to retrieve and apply correction tendencies specific to the current form type, improving correction accuracy without requiring a complete system redesign. The segmentation is implemented through identifying form features from the form image and selecting corresponding correction tendencies from multiple accumulated groups.
Solution Approach 2:
The patent applies preliminary action by accumulating and organizing correction tendencies for different form features in advance. Before actual correction is needed, the system pre-processes and stores correction patterns specific to each form type. When a form is presented for correction, the system simply retrieves the pre-organized correction tendencies matching the form's features, avoiding complex real-time analysis while maintaining high accuracy.
2Measurement precision
If correction tendencies are accumulated for all form types without differentiation, then the data accumulation is comprehensive, but the relevant correction information cannot be retrieved accurately for specific form fields
Solution Approach 1:
The patent segments the accumulated correction data by form features, creating separate correction tendency accumulations for different form types (medical forms, financial forms, etc.). This segmentation allows the system to retrieve only the relevant correction data for the current form type, improving retrieval accuracy while managing data volume efficiently through organized categorization.
Solution Approach 2:
The patent applies local quality by providing different correction tendencies for different form features. Instead of using a single uniform correction approach for all forms, the system tailors the correction tendencies to match the specific form type being processed. This ensures that the correction information retrieved is locally optimized for each form's specific requirements and characteristics.
3Measurement precision
If form features are identified and correction tendencies are accumulated separately for each form type, then the correction accuracy is improved, but the device complexity and processing time increase
Solution Approach 1:
The patent applies preliminary action by pre-accumulating and organizing correction tendencies for different form features before actual correction is needed. The system pre-processes form images to identify form features and stores correction tendencies in organized groups. When correction is required, the system simply retrieves the pre-organized tendencies matching the form type, avoiding time-consuming real-time analysis while maintaining high accuracy.
Solution Approach 2:
The patent uses copying by storing correction tendencies as reusable patterns for different form types. Once correction tendencies are identified for a particular form type, they are copied and stored for future use with similar forms. This eliminates the need to re-analyze and re-determine correction patterns for each new form, significantly reducing processing time while maintaining consistent accuracy across similar form types.
Data Source
AI summary
An information processing apparatus includes a processor. The processor is configured to identify, from a character string recognition result for a form, a form feature that indicates at least a field in which the form is used or an attribute of a filling-out person filling out the form, accumulate past correction tendencies for character string recognition results for forms having respective identified form features, and obtain a correction tendency for a form having a form feature that is the same as the identified form feature from among the accumulated correction tendencies, and perform control to display a candidate correct expression for the character string recognition result for the form in accordance with the obtained correction tendency.