Relaxed functional dependencies (rfds) are properties expressing important relationships among data. Thanks to the introduction of approximations in data comparison and/or validity, they can capture constraints useful for several purposes, such as the identi fication of data inconsistencies or patterns of semantically related data. Nevertheless, rfds can provide benefits only if they can be automatically discovered from data. In this discussion paper we present an rfd discovery algorithm relying on a lattice structured search space, and a new candidate rfd validation method. An experimental evaluation demonstrates the discovery performances of the proposed algorithm on real datasets.
Lattice-based Discovery of Hybrid Relaxed Functional Dependencies
Caruccio L.;Deufemia V.;Polese G.
2020-01-01
Abstract
Relaxed functional dependencies (rfds) are properties expressing important relationships among data. Thanks to the introduction of approximations in data comparison and/or validity, they can capture constraints useful for several purposes, such as the identi fication of data inconsistencies or patterns of semantically related data. Nevertheless, rfds can provide benefits only if they can be automatically discovered from data. In this discussion paper we present an rfd discovery algorithm relying on a lattice structured search space, and a new candidate rfd validation method. An experimental evaluation demonstrates the discovery performances of the proposed algorithm on real datasets.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
