PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Lattice Characterization of Armstrong and Symmetric Dependencies
Jaume Baixeries
(2007) PhD thesis, Universitat Politecnica de Catalunya.

Abstract

Dependencies 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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EPrint Type:Thesis (PhD)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Theory & Algorithms
ID Code:3333
Deposited By:Jaume Baixeries
Deposited On:08 February 2008