Acquiring expert rules with the aid of decision tables

This paper describes a computer-assisted approach to help knowledge engineers elicit rules from a domain expert. The approach uses the decision table as a knowledge engineering tool, and incorporates a decision table analyzer that displays rule conditions which can be used to query the expert. The decision table analyzer also reports redundant rules and provides assistance for developing rules that use as few variables as possible. This has the benefit of limiting the number of questions to be asked of the expert. The approach is especially suited for heuristic classification problems where evaluative judgements are based on many combinations of values of the same facts.