A fuzzy reasoning approach to support knowledge acquisition

Acquisition of a user's computer based problem-solving skill is an important research area in human-computer interaction. This type of information usually can be derived by careful inspection on the actual dialog behavior. To implement such a knowledge reasoning agent, several crucial issues are pointed out and carefully inspected. These include: (a) appropirtate knowledge representation schema that are able to demonstrate the causal relationship between pairs of dialog events; (b) the formulation of a valid formula in calculating the overall knowledge index from the background information; (c) determination of the minimum sufficient number of dialog events required to form a discernible pattern; and (d) generalization of categories of performance patterns that can be applied to all types of application domains. A prototype reasoning agent based on the proposed methodology is constructed and its effectiveness is verified with the dialog events during UNIX operations.