Abstract
Data dependencies play an important role in the design of relational databases. There is a strong connection between dependencies and some fragments of the propositional logic. In particular, functional dependencies are closely related to Horn formulas. Also, multivalued dependencies are characterized in terms of multivalued formulas. It is known that both Horn formulas and sets of functional dependencies are learnable in the exact model of learning with queries. Here we present an algorithm that learns a non-trivial subclass of multivalued formulas using membership and equivalence queries. Furthermore, a slight modification of the algorithm allows us to learn the corresponding subclass of multivalued dependencies.
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