Dynamic Inference Rule Insertion in Information Bases
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing information systems lack dynamic modification capabilities for deduction engines and inference rules, requiring static introduction and modification by authorized administrators, which slows down the information extraction process and fails to address contradictions in combined information bases.
Innovation Solution
A method and apparatus for dynamically inserting or removing inference rules and deduction engines, validated through signature authentication, allowing authorized agents to modify these components on demand, ensuring secure and efficient information extraction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If deduction engines and inference rules are statically introduced in the system, then system security and control are maintained, but modification speed and adaptability are reduced
Solution Approach 1:
The patent transforms the static nature of deduction engines and inference rules into a dynamic system where authorized agents can modify rules in real-time. The system maintains a distinction between static core components and dynamic modifiable rules, allowing the rule set to adapt continuously while the underlying engine structure remains stable.
Solution Approach 2:
The system separates deduction engines from inference rules, allowing rules to be independently modified without affecting the core engine architecture. This segmentation enables fine-grained control where specific rules can be added, removed, or updated by authorized agents while the engine itself remains intact and secure.
2Measurement precision
If authorized system administrators modify inference rules, then accuracy of information extraction is improved, but processing time increases
Solution Approach 1:
The system performs preliminary validation and authorization checks before rule modifications are applied. By pre-establishing authorization mechanisms and validation protocols, the system minimizes the time required for actual rule modifications, as the framework for secure modification is already in place and ready to execute changes immediately.
Solution Approach 2:
Authorized agents can independently modify inference rules without requiring system administrator intervention for each change. The system empowers authorized users to perform modifications themselves through predefined authorization levels, eliminating the time-consuming intermediary step of administrator approval for routine rule updates.
3Loss of information
If multiple information bases are combined, then information completeness is improved, but contradiction detection and resolution become more difficult
Solution Approach 1:
The system implements feedback mechanisms that monitor inference rules across multiple information bases for contradictions. When potential conflicts are detected, the system provides feedback to authorized agents who can review and resolve the contradictions by modifying the appropriate rules, ensuring consistency across integrated information sources.
Solution Approach 2:
The deduction engine acts as an intermediary layer between multiple information bases, mediating the integration process. It applies inference rules uniformly across different sources and identifies contradictions that arise from combining information bases with different rule sets, allowing systematic resolution of conflicts.
Data Source
AI summary
An approach is provided for dynamic modification of inference rules and deduction engines in an information base. Authorized agents are allowed to insert, delete or modify inference rules and deduction engines dynamically by signing their input using an authorized signature. Additionally, the functionalities of dynamic modification of inference rules and deduction engines can be provided through a direct application programming interface (API).