Knowledge Database Contradiction Processing

Solution Overview

Problem

Existing computing systems face challenges in efficiently processing and analyzing large volumes of text data due to issues like data accuracy, interpretation of regional dialects, and the ambiguity inherent in words.

Innovation Solution

The system employs a computing framework that includes AI servers, transactional servers, and user devices, utilizing pattern recognition techniques, statistical reasoning, and advanced modules like the collections module, IEI module, and query module to interpret content, process queries, and generate responses.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If pattern recognition techniques and statistical reasoning are used to process text data, then the ability to handle ambiguities and interpret regional dialects is improved, but the computational complexity and processing time increase

Engineering Contradiction:

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system segments text processing into multiple specialized modules: a collections module for gathering data, an IEI (Interpretive Expression Interpreter) module for semantic analysis, and a query module for generating responses. Each module handles specific aspects of text processing, allowing the system to manage computational complexity through functional decomposition while maintaining high adaptability for handling ambiguities and dialects.

Inventive Principle:

Principle #1Segmentation

2Measurement precision

If advanced modules like collections module, IEI module, and query module are employed to extract knowledge from content, then the accuracy and relevance of query responses are improved, but the system complexity and resource requirements increase

Engineering Contradiction:

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The collections module, IEI module, and query module are designed as universal components that can handle multiple types of text data and query scenarios. The IEI module, in particular, serves multiple functions including semantic interpretation, ambiguity resolution, and dialect recognition, allowing the system to maintain high response accuracy without proportionally increasing overall system complexity through functional consolidation.

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Productivity

If the system processes large volumes of text data using multiple servers and modules, then the knowledge extraction capability is improved, but the processing time and computational resources increase

Engineering Contradiction:

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The collections module performs preliminary actions by gathering and pre-processing text data before it reaches the IEI and query modules. This includes initial filtering, normalization, and organization of text data, which reduces the computational burden on subsequent modules and accelerates the overall knowledge extraction process while maintaining high productivity.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20250077907A1Processing a contradiction in a knowledge database

Publication Date: 2025.03.06

AI summary

A method includes generating a content entigen group for content using identigen pairing rules. The method further includes obtaining a contradicting entigen group based on the content entigen group. The method further includes updating the knowledge database to include the content entigen group. A contradicted entigen of the content entigen group is established to indicate duplication of a contradicted entigen of the contradicting entigen group.