The development and application of a knowledge modelling technique

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Abstract
Knowledge acquisition is a major bottleneck in the efficient development of knowledge-based systems because knowledge engineers are often faced with die difficult task of creating a conceptual model of a domain unfamiliar to them. In this paper, we propose a systematic technique which would help the knowledge engineer in this difficult modelling task. We discuss development of the knowledge modelling technique which involved a synthesis of both empirical observations obtained in a case study and theoretical insights gleaned from some artificial intelligence literature. The result of the juxtaposition is the formulation of a domain-independent categorization of knowledge types and inferences, which we called the inferential model. The model serves as a template of the types of knowledge in a model of expertise. Based on the model, we derived the inferential modelling technique which facilitates analysing verbal data elicited from an expert and configuring the data into a conceptual model. The technique is applied for analysis of knowledge obtained in the case study and we demonstrate its utility in organizing the elements of knowledge. Finally we suggest how the technique differs from other knowledge modelling approaches and some weaknesses in the present version of the model.

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