Preferred database repairs under aggregate constraints

A framework for computing preferred repairs in numerical databases violating a given set of strong and weak aggregate constraints is introduced, which is based on a transformation into an Integer Linear Programming (ILP) instance. Aggregate constraints are linear inequalities on aggregates retrieved from the input data. While strong constraints express mandatory conditions, weak constraints define conditions which are expected to be satisfied, even if this is not mandatory. Thus, preferred repairs are repairs which make the data satisfy all the given strong constraints and as many weak constraints as possible. An experimental validation of the proposed approach is provided, proving its effectiveness. © Springer-Verlag Berlin Heidelberg 2007.