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Conceptual 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 han...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autores principales: Ganter, Bernhard (Autor), Obiedkov, Sergei (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2016.
Edición:1st ed. 2016.
Temas:
Acceso en línea:Texto Completo

MARC

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245 1 0 |a Conceptual Exploration  |h [electronic resource] /  |c by Bernhard Ganter, Sergei Obiedkov. 
250 |a 1st ed. 2016. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2016. 
300 |a XVII, 315 p. 148 illus.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
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505 0 |a 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. . 
520 |a 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. 
650 0 |a Data mining. 
650 0 |a Algebra. 
650 1 4 |a Data Mining and Knowledge Discovery. 
650 2 4 |a Order, Lattices, Ordered Algebraic Structures. 
700 1 |a Obiedkov, Sergei.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
710 2 |a SpringerLink (Online service) 
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