Preprint
Iceberg query lattices for datalog
Zusammenfassung
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.
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.
Zitieren
@article{urn:nbn:de:hebis:34-2009031726692,
author={Stumme, Gerd},
title={Iceberg query lattices for datalog},
year={2004}
}
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2009-03-17T08:25:43Z 2009-03-17T08:25:43Z 2004 urn:nbn:de:hebis:34-2009031726692 http://hdl.handle.net/123456789/2009031726692 153240 bytes application/pdf eng Urheberrechtlich geschützt https://rightsstatements.org/page/InC/1.0/ 004 Iceberg query lattices for datalog Preprint 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. open access Stumme, Gerd 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) Data Mining Formale Begriffsanalyse
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