Inductive certainty factors from databases

EPficient use of intelligent information systems nzquires tools that can ass& not only in finding information that can be deduced from the databases, but also in inferring missing information using similatity and statistical-based measures adapted from artificial intell igence. Inductive dependencies provide an expressive way to achieve this goal. Relationships that are not functional can be v&ten precisely, and a delta measurement makes explicit the reliability of the relationship. Using inductive dependencies and appropriate delta-functions one can express a wide spectrum of relationships and manipulate them with some degree of certainty. In this paper, we discuss the utility of inductive dependency as a knowledge mining formalism that can be used in discovery in databases and study properties of delta functions that capture the @actionality of relationships. B’s certainty by m”. Bayesian probability systems[l7] use rules of this form to express “among the worlds where A is satisfied, those that also satisfy B are in a m-percent majority”.