Structured Task Database Using Selective Data Extraction Rules

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Solution Overview

Problem

Existing methods for generating a target database from a set of source databases are not optimal, leading to inefficiencies in data extraction and processing during critical situations, particularly when users are constrained by time or stress, resulting in the potential for inappropriate decision-making due to incomplete data analysis.

Innovation Solution

A method and electronic device that generate a structured database by acquiring extraction rules based on required actions, selecting relevant rules, sending extraction laws to databases, storing received data in organized classes, and associating unsuccessful queries, allowing for efficient and appropriate data extraction.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If all data from source databases is extracted and stored in the target database, then the completeness of data is improved, but the time required for data extraction and processing increases

Engineering Contradiction:

Improvecompleteness of dataVSAvoidtime required for data extraction

Core Design Contradiction:

Loss of informationVSLoss of time

Solution Approach 1:

The patent extracts only the relevant data elements needed for the specific task from the source databases, rather than extracting all available data. This is achieved through a selection mechanism that identifies and extracts only the necessary data elements based on the task requirements, thereby reducing extraction time while maintaining data completeness for the specific purpose.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent segments the data extraction process into distinct categories or types of data elements. By organizing the extraction into segments based on data type or relevance category, the system can efficiently process and extract only the necessary segments required for the task, reducing overall extraction time while ensuring all necessary data categories are covered.

Inventive Principle:

Principle #1Segmentation

2Measurement precision

If extraction rules are manually created and maintained, then the precision of data extraction is improved, but the complexity of the system increases

Engineering Contradiction:

Improveprecision of data extractionVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent implements a self-updating mechanism for extraction rules that automatically adapts to changes in source databases without requiring manual intervention. The system monitors database structure changes and automatically updates the extraction rules to maintain precision, thereby reducing system complexity while preserving extraction accuracy.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The extraction rules are designed to be dynamic and adaptive rather than static. The system automatically adjusts extraction rules based on changes in the source databases or task requirements, maintaining precision without requiring manual rule creation and maintenance. This dynamic approach reduces the burden of system management while preserving extraction accuracy.

Inventive Principle:

Principle #15Dynamics

3Adaptability or versatility

If the target database contains all possible data elements, then the versatility of the database is improved, but the time required to analyze and process the data increases

Engineering Contradiction:

Improveversatility of databaseVSAvoidtime required for data analysis

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The patent applies partial action by extracting and storing only the specific data elements required for the given task, rather than all possible data elements. This selective approach maintains versatility for the specific purpose while significantly reducing the time required to analyze and process the data, as the user is presented with only the relevant information needed for decision-making.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS20260003831A1Method and electronic device for generating a structured database of relevant data for managing a task, and associated computer program

Publication Date: 2026.01.01 THALES SA

AI summary

Generating, from a set of databases, a structured database associated with a task, including acquiring a list of required action(s) and a group of data extraction rules each including an extraction law, generating a structure of the structured database including at least one class of unsuccessful queries, sending the extraction rule(s) to the set and receiving extracted data from the set, storing the or each received extracted data in a class of the structured database, and for each sent extraction law, if no retrieved data is received in response from the set, associating the law with the class of unsuccessful queries.