Overview
- Self contained, with numerous examples
- Research, but nevertheless practical
- A broad methodology of conceptual knowledge acquisition
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Table of contents (6 chapters)
Keywords
About this book
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.
Reviews
“The book is a very pleasant and interesting reading on attribute exploration from formal concept analysis. Reading it, I felt that all the theoretical background is thoroughly described and always accompanied with many explanations. It also abounds in very illustrative examples, whose solutions are given step by step. … This is a book written with a lot of enthusiasm all of which will be transferred to its readers.” (Catalin Stoean, zbMATH 1357.68004, 2017)
Authors and Affiliations
About the authors
Bernhard Ganter is emeritus professor of mathematics at Technische Universität Dresden, Germany. His main research field is Formal Concept Analysis.
Sergei Obiedkov is an associate professor at the National Research University Higher School of Economics, Moscow. His research covers topics in data analysis and artificial intelligence, including logical and algorithmic aspects.
Bibliographic Information
Book Title: Conceptual Exploration
Authors: Bernhard Ganter, Sergei Obiedkov
DOI: https://doi.org/10.1007/978-3-662-49291-8
Publisher: Springer Berlin, Heidelberg
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2016
Hardcover ISBN: 978-3-662-49290-1Published: 06 June 2016
Softcover ISBN: 978-3-662-56999-3Published: 30 May 2018
eBook ISBN: 978-3-662-49291-8Published: 26 May 2016
Edition Number: 1
Number of Pages: XVII, 315
Number of Illustrations: 148 b/w illustrations
Topics: Data Mining and Knowledge Discovery, Order, Lattices, Ordered Algebraic Structures