Techniques for data and rule validation in knowledge based systems

Abstract

A framework is proposed for the validation of data and rules in knowledge-based systems. This work involves three major tasks: (1) validation of data; (2) validation of rules; and (3) interaction between data and rule validation. These tasks are conducted on a rule set that specifies the dependencies of rule variables. Data validation is performed by using the enforcement of constraint rules. Constraint rules are also propagated for the overall database consistency. A scheme for rule validation is sketched. The completeness and consistency of rules are verified by a theorem-proving method. It is concluded that production rules should be restricted by constraint rules, whereas constraint rules can correct the inconsistency of data by reasoning production rules.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>