A Practical Formalism for Imprecise Inference Control

This paper describes a powerful, yet practical, formalism for modeling and controlling imprecise FD-based inference in relational database systems. The formalism provides a canonical representation of inference which unifies precise inference and the primitive imprecise inference mechanisms of abduction and partial deduction. Whereas other imprecise (partial) inference models estimate the probability of making inferences, the formalism supports the analysis of the actual imprecise values inferred in a database extension. Imprecise inference is analyzed by transforming a precise database augmented with additional "catalytic" relations, conveying possibly imprecise a priori knowledge, into an equivalent imprecise database. The analysis of imprecise inference and the related inference control methodology are highly flexible and robust. They can be directly applied to classical, MLS, and imprecise databases. With minimal modifications, they also can be used in knowledge discovery or databa..