Abstract:
Probabilistic databases address well the requirements of an increasing number of modern applications that produce large volumes of uncertain data from a variety of sources. Probabilistic keys enforce the integrity of entities in order to facilitate data processing in probabilistic database systems. For this purpose, we establish algorithms for an agile schema-and data-driven elicitation of the marginal probability by which keys should hold in a given application domain, and for reasoning about these keys. The efficiency of our elicitation framework is demonstrated theoretically and experimentally.