Database dependency discovery: a machine learning approach

this paper are designed such that they can easily be generalised to other kinds of dependencies. Like in current approaches to computational induction such as inductive logic programming, we distinguish between topdown algorithms and bottom-up algorithms. In a top-down approach, hypotheses are generated in a systematic way and then tested against the given relation. In a bottom-up approach, the relation is inspected in order to see what dependencies it may satisfy or violate. We give algorithms for both approaches. Keywords: Induction, attribute dependency, database reverse engineering, data mining. 1. Introduction