Conceptual Exploration
Ganter, Bernhard
Conceptual Exploration by Bernhard Ganter, Sergei Obiedkov - Berlin, Heidelberg Springer Berlin Heidelberg 2016 - 1 recurso en línea (XVII, 315 p.) 148 ilustraciones
What to expect from this book -- Concept lattices -- An algorithm for closure systems -- The canonical basis -- Attribute exploration -- Non-implicational background knowledge -- Enhancing the expressive power -- Relational Exploration -- Concept exploration
This is the first textbook on attribute exploration, its theory, its algorithms for applications, and some of its many possible generalizations. Attribute exploration is useful for acquiring structured knowledge through an interactive process, by asking queries to an expert. Generalizations that handle incomplete, faulty, or imprecise data are discussed, but the focus lies on knowledge extraction from a reliable information source. The method is based on Formal Concept Analysis, a mathematical theory of concepts and concept hierarchies, and uses its expressive diagrams. The presentation is self-contained. It provides an introduction to Formal Concept Analysis with emphasis on its ability to derive algebraic structures from qualitative data, which can be represented in meaningful and precise graphics
9783662492918
Data mining
Álgebra
QA76.9.D343 / G368 2016 EB
006.312
Conceptual Exploration by Bernhard Ganter, Sergei Obiedkov - Berlin, Heidelberg Springer Berlin Heidelberg 2016 - 1 recurso en línea (XVII, 315 p.) 148 ilustraciones
What to expect from this book -- Concept lattices -- An algorithm for closure systems -- The canonical basis -- Attribute exploration -- Non-implicational background knowledge -- Enhancing the expressive power -- Relational Exploration -- Concept exploration
This is the first textbook on attribute exploration, its theory, its algorithms for applications, and some of its many possible generalizations. Attribute exploration is useful for acquiring structured knowledge through an interactive process, by asking queries to an expert. Generalizations that handle incomplete, faulty, or imprecise data are discussed, but the focus lies on knowledge extraction from a reliable information source. The method is based on Formal Concept Analysis, a mathematical theory of concepts and concept hierarchies, and uses its expressive diagrams. The presentation is self-contained. It provides an introduction to Formal Concept Analysis with emphasis on its ability to derive algebraic structures from qualitative data, which can be represented in meaningful and precise graphics
9783662492918
Data mining
Álgebra
QA76.9.D343 / G368 2016 EB
006.312