Knowledge-based Knowledge Elicitation

Abstract

A method for using the advantages of domain-specific knowledge acquisition for a general purpose knowledge acquisition tool is introduced. To adapt the knowledge acquisition tool for a specific application and a specific problem solving strategy (e .g . heuristic classification, such diagnostic strategies as establish and refine), acquisition knowledge bases (AKBs) are integrated in the system to guide the employment of different knowledge elicitation methods (interview techniques, protocol analysis, semantic text analysis and learning mechanisms). Acquisition knowledge bases are predefined deep models, consisting of structured objects to represent important concepts of a domain . These knowledge bases are used in addition to the already acquired knowledge to trigger specific elicitation methods by an analysis of incompleteness and inconsistency of the existing knowledge in the system. Furthermore, methods for integrating these kinds of knowledge acquisition tools with machine learning approaches are discussed .