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(2004) Conceptual structures at work, Dordrecht, Springer.
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.
Publication details
DOI: 10.1007/978-3-540-27769-9_7
Full citation:
Stumme, G. (2004)., Iceberg query lattices for datalog, in K. E. Wolff, H. D. Pfeiffer & H. Delugach (eds.), Conceptual structures at work, Dordrecht, Springer, pp. 109-125.
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