Rules Collector System for Conversational Knowledge Formalization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current rules engines and knowledge-based systems lack the capability to formalize an individual's expertise, update rules automatically, and provide a conversational mode for continuous knowledge sharing and integrity testing of newly formulated rules.
Innovation Solution
A rules collector system that includes a rules retrieval coordinator for bidirectional information exchange, a rules input processor with voice recognition, a rules generator, a rule integrity check subsystem, and a situational test generator, enabling real-time creation and updating of rules through conversational interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual rule population methods are used, then system implementation is simple, but knowledge cannot be continuously updated and formalized
Solution Approach 1:
The system enables self-service by automatically formalizing individual knowledge through conversational interactions. The rules retrieval coordinator and rules generator work together to capture, structure, and store knowledge without requiring manual intervention from system administrators, allowing the system to update itself continuously
Solution Approach 2:
The system implements feedback mechanisms where conversational inputs from individuals are processed through the rules input processor, analyzed by the rules generator, validated by the rule integrity check subsystem, and stored in the rules engine. This closed-loop feedback enables continuous knowledge refinement and system improvement
2Adaptability or versatility
If traditional rules engines are used, then system structure is simple, but conversational mode and continuous learning are not supported
Solution Approach 1:
The system achieves multi-functionality by integrating multiple capabilities into a unified architecture: the rules retrieval coordinator handles conversational interactions, the rules input processor captures various input formats, the rules generator creates formal rules, and the rule integrity check subsystem validates them. This universal system performs knowledge capture, processing, validation, and storage through a single integrated platform
Solution Approach 2:
The rules retrieval coordinator acts as an intermediary between users and the rules engine, translating conversational inputs into structured rule definitions. Similarly, the rules input processor serves as a mediator that bridges natural language communication and formal rule representation, enabling seamless knowledge transfer
3Productivity
If new rules are added without testing, then rule implementation is fast, but rule integrity cannot be ensured
Solution Approach 1:
The system performs preliminary actions by automatically testing new rules through the situational test generator before they are fully implemented. The rule integrity check subsystem validates rules against existing knowledge bases and constraints, identifying potential conflicts or errors before the rules are activated in production, thus preventing faulty rules from degrading system performance
Solution Approach 2:
The automated testing and validation process allows the system to rapidly verify rule integrity without manual intervention. The situational test generator quickly evaluates multiple scenarios, and the rule integrity check subsystem rapidly validates rules against the knowledge base, enabling fast yet reliable rule implementation
Data Source
AI summary
A rules collector system and method. The system and method enables a process of capturing an expertise of an individual in a formalized manner, and which may update rules and knowledge databases with information based on the interaction with the individual. The system includes a rules retrieval coordinator responsive to an input from an individual and adapted to provide relevant information to the individual based on the input and to enable a bidirectional information exchange with the individual. A rules input processor is used for monitoring responses from the individual and generating one of a plurality of different outputs depending on the responses. A rules generator is responsive to the rules input processor and is used to form one or more new rules based on the responses from the individual. A rule integrity check subsystem automatically checks integrity of the new rule based on pre-existing rules.