In this paper we study two orthogonal extensions of the classical data
mining problem of mining association rules, and show how they naturally interact.
The first is the extension from a propositional representation to datalog, and
the second is the condensed representation of frequent itemsets by means of Formal
Concept Analysis (FCA). We combine the notion of frequent datalog queries
with iceberg concept lattices (also called closed itemsets) of FCA and introduce
two kinds of iceberg query lattices as condensed representations of frequent datalog
queries. We demonstrate that iceberg query lattices provide a natural way to
visualize relational association rules in a non-redundant way.
Auch erschienen in: Wolff, Karl Erich u.a. (Hrsg.): Conceptual structures at work. (Lecture notes in computer science ; 3127). Berlin u.a. : Springer, 2004. S. 109-125. ISBN 3-540-22392-4 (The original publication is available at www.springerlink.com)