Affiliations: [a] Computer Science Department, Faculty of Sciences of Tunis, University of Tunis El Manar, Tunisia | [b] Laboratoire d'Informatique Fondamentale de Marseille, Aix-Marseille, Université IUT d'Aix en Provence, France
Correspondence:
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Corresponding author: Ghada Gasmi, Computer Science Department, Faculty of Sciences of Tunis, University of Tunis El Manar, Tunisia. E-mail: [email protected]
Abstract: A general assumption in all existing algorithms permitting to mine functional dependencies is that the database is static. However, real life databases are frequently updated. To the best of our knowledge, the discovery of functional dependencies in dynamic databases has never been studied. A naïve solution consists in re-applying one of the existing algorithms to discover functional dependencies holding on the updated database. Nevertheless, in many domains, where response time is crucial, re-executing algorithms from scratch would be inacceptable. In this paper, we propose a new technique that makes use of the previously discovered results to cut down the amount of work that has been done to discover the new set of functional dependencies satisfied by the updated database.
Keywords: Functional dependencies, evolving databases, data mining, knowledge discover, maintenance
