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Conceptual exploration

Ganter, Bernhard.

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Conceptual exploration

Record Type:	Electronic resources : Monograph/item
Title/Author:	Conceptual exploration/ by Bernhard Ganter, Sergei Obiedkov.
Author:	Ganter, Bernhard.
other author:	Obiedkov, Sergei.
Published:	Berlin, Heidelberg :Springer Berlin Heidelberg : : 2016.,
Description:	xvii, 315 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer eBooks
Subject:	Attribute focusing (Data mining) -
Online resource:	http://dx.doi.org/10.1007/978-3-662-49291-8
ISBN:	9783662492918

Conceptual exploration
Ganter, Bernhard.

Conceptual exploration[electronic resource] /by Bernhard Ganter, Sergei Obiedkov. - Berlin, Heidelberg :Springer Berlin Heidelberg :2016. - xvii, 315 p. :ill., digital ;24 cm.

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.

ISBN: 9783662492918

Standard No.: 10.1007/978-3-662-49291-8doiSubjects--Topical Terms:

2194851
Attribute focusing (Data mining)

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Conceptual exploration
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100 1 $a Ganter, Bernhard. $3 892574
245 1 0 $a Conceptual exploration $h [electronic resource] / $c by Bernhard Ganter, Sergei Obiedkov.
260 $a Berlin, Heidelberg : $b Springer Berlin Heidelberg : $b Imprint: Springer, $c 2016.
300 $a xvii, 315 p. : $b ill., digital ; $c 24 cm.
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 Attribute focusing (Data mining) $3 2194851
650 0 $a Mathematical analysis. $3 516833
650 0 $a Concept mapping. $3 1005822
650 1 4 $a Computer Science. $3 626642
650 2 4 $a Data Mining and Knowledge Discovery. $3 898250
650 2 4 $a Order, Lattices, Ordered Algebraic Structures. $3 896039
700 1 $a Obiedkov, Sergei. $3 901056
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
856 4 0 $u http://dx.doi.org/10.1007/978-3-662-49291-8
950 $a Computer Science (Springer-11645)