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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.
List of contents
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.
About the author
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.
Summary
This is the first textbook on attribute exploration, its theory, its algorithms forapplications, and some of its many possible generalizations. Attribute explorationis useful for acquiring structured knowledge through an interactive process, byasking queries to an expert. Generalizations that handle incomplete, faulty, orimprecise data are discussed, but the focus lies on knowledge extraction from areliable information source.The method is based on Formal Concept Analysis, a mathematical theory ofconcepts and concept hierarchies, and uses its expressive diagrams. The presentationis self-contained. It provides an introduction to Formal Concept Analysiswith emphasis on its ability to derive algebraic structures from qualitative data,which can be represented in meaningful and precise graphics.
Additional text
“The book reads smoothly, emphasizes examples over theorems, and has pictures (mainly of concept lattices) and tables galore. … I thus recommend it to all researchers concerned with FCA or query learning.” (Marcel Wild, Mathematical Reviews, May, 2017)
“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)
Report
"The book reads smoothly, emphasizes examples over theorems, and has pictures (mainly of concept lattices) and tables galore. ... I thus recommend it to all researchers concerned with FCA or query learning." (Marcel Wild, Mathematical Reviews, May, 2017)
"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)
