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Efficient Discovery of Functional Dependencies and Armstrong Relations

Abstract : In this paper, we propose a new efficient algorithm called Dep-Miner for discovering minimal non-trivial functional dependencies from large databases. Based on theoretical foundations, our approach combines the discovery of functional dependencies along with the construction of real-world Armstrong relations (without additional execution time). These relations are small Armstrong relations taking their values in the initial relation. Discovering both minimal functional dependencies and real-world Armstrong relations facilitate the tasks of database administrators when maintaining and analyzing existing databases. We evaluate Dep-Miner performances by using a new benchmark database. Experimental results show both the efficiency of our approach compared to the best current algorithm (i.e. Tane), and the usefulness of real-world Armstrong relations.
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Contributor : Stéphane Lopes <>
Submitted on : Wednesday, April 9, 2008 - 2:41:35 PM
Last modification on : Monday, January 20, 2020 - 12:12:05 PM

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Stéphane Lopes, Jean-Marc Petit, Lotfi Lakhal. Efficient Discovery of Functional Dependencies and Armstrong Relations. Extending Database Technology (EDBT), Mar 2000, Konstanz, Germany. pp.350-364, ⟨10.1007/3-540-46439-5_24⟩. ⟨hal-00271567⟩



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