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.
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.
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 givl#,
![Conceptual Exploration [Hardcover]](/itemImage/2/6/5/0/2_990257.jpg)