Towards Method-Independent Knowledge Acquisition

Rapid prototyping and tool reusability h a v e pushed knowledge acquisition research to investigate method-specic knowledge acquisition tools appropriate for predetermined problem-solving methods. We believe that method-dependent knowledge acquisition is not the only approach. The aim of our research i s t o d e v elop powerful yet versatile machine learning mechanisms that can be incorporated into general-purpose but practical knowledge acquisition tools. This paper shows through examples the practical advantages of this approach. In particular, we illustrate how existing knowledge can be used to facilitate knowledge acquisition through analogy mechanisms within a domain and across domains. Our sample knowledge acquisition dialogues with a domain expert illustrate which parts of the process are addressed by the human and which parts are automated by the tool, in a synergistic cooperation for knowledge-base extension and renement. The paper also describes brie BLOCKINy the problem-solving architecture that facilitates this approach t o k n o wledge acquisition.