Database Construction for Sensitivity Information Analysis
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Solution Overview
Problem
Current systems lack the ability to effectively learn about the relationship between multiple entities and their associated sensitivity information from a database constructed from texts related to these entities.
Innovation Solution
An information management system that translates and filters public information from multiple languages into a designated language, extracts sensitivity information, and constructs a database associating it with the translated texts, allowing for keyword-based searches and visualization of sensitivity information occurrence frequencies across different categories and time periods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a database is constructed from texts related to multiple entities without translation and sensitivity analysis, then the system is simple and fast to build, but the system cannot effectively learn about the relationship between entities and sensitivity information
Solution Approach 1:
The patent segments the database construction process into distinct functional modules: text acquisition unit, translation unit, sensitivity information extraction unit, and database construction unit. Each module handles a specific aspect of processing, allowing the system to systematically handle multilingual texts and extract sensitivity information while maintaining manageable complexity through functional decomposition
Solution Approach 2:
The patent applies preliminary action by performing translation of texts into the target language before extracting sensitivity information. This preprocessing step ensures that all texts are in a uniform language state, enabling effective sensitivity analysis to be conducted on translated content, thereby preserving sensitivity information relationships across multiple entities
2Measurement precision
If sensitivity information is extracted and classified for each text, then the system can provide detailed sensitivity analysis, but the processing time and computational resources increase
Solution Approach 1:
The patent segments sensitivity information into multiple classification categories (e.g., personal information, commercial secrets, national security). This segmentation allows the system to process and classify different types of sensitivity information independently, improving measurement precision through detailed categorization while managing processing time by handling classifications in an organized manner
Solution Approach 2:
The patent extracts and classifies sensitivity information for each individual text in the collection. This partial action approach ensures comprehensive sensitivity analysis coverage, achieving high measurement precision by examining each text's sensitivity characteristics separately, even though it increases overall processing time
3Adaptability or versatility
If the system processes and stores sensitivity information for multiple entities, then the system provides comprehensive analysis capability, but the database size and storage requirements increase
Solution Approach 1:
The patent organizes the database structure by segmenting data storage into entity-specific sections, each containing texts and their associated sensitivity information. This segmentation enables the system to handle multiple entities with their respective sensitivity profiles, providing comprehensive multi-entity analysis capability while managing storage requirements through structured organization
Solution Approach 2:
The patent creates a universal database structure that can handle multiple entities and various types of sensitivity information through a standardized schema. This multi-functional design allows the same database structure to accommodate different entities and sensitivity categories, enhancing adaptability without requiring separate storage systems for each entity type
Data Source
AI summary
An information management system is provided. An occurrence frequency of sensitivity information over a designated period that is associated with each of designated texts and stored in a database is evaluated over the designated period and a plurality of designated unit periods constituting the designated period for each sensitivity category. Then, a reference image showing the evaluation result is generated and transmitted to an information terminal device, and the reference image about each of a plurality of entities is simultaneously outputted on an output interface of the information terminal device.