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Lattice Characterization of Armstrong and Symmetric Dependencies AbstractDependencies are restrictions or constraints that apply to a set of data. They can be found in different realms: Database Theory, Data Mining, Artificial Intelligence, Propositional Logic, etc. Lattice characterization of dependencies has been studied from two different points of view: its theoretical foundations and its applications, mainly in the fields of database theory and knowledge discovery. In the first part of this thesis, we present a generic and modular lattice characterization of a set of Armstrong and symmetric dependencies, from a semantic and a syntactical point of view, in terms of Formal Concept Analysis, a formalism used in knowledge discovery. In the second part of this thesis, two applications of those lattice characterizations are also presented: the definition of Armstrong relations for Armstrong and symmetric dependencies, and the definition of a formal context for symmetric dependencies.
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