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Iceberg Query Lattices for Datalog

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Book cover Conceptual Structures at Work (ICCS 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3127))

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Abstract

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.

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Author information

Authors and Affiliations

  1. Knowledge & Data Engineering Group, Department of Mathematics & Computer Science, University of Kassel, D–34121, Kassel, Germany

    Gerd Stumme

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  1. Gerd Stumme
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Editors and Affiliations

  1. Mathematics and Science Faculty, Darmstadt University of Applied Sciences, Schoefferstr. 3, D-64295, Darmstadt, Germany

    Karl Erich Wolff

  2. New Mexico State University,  

    Heather D. Pfeiffer

  3. Computer Science Department, Univ. of Alabama in Huntsville, AL 35899, Huntsville

    Harry S. Delugach

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Stumme, G. (2004). Iceberg Query Lattices for Datalog. In: Wolff, K.E., Pfeiffer, H.D., Delugach, H.S. (eds) Conceptual Structures at Work. ICCS 2004. Lecture Notes in Computer Science(), vol 3127. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27769-9_7

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  • DOI: https://doi.org/10.1007/978-3-540-27769-9_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22392-4

  • Online ISBN: 978-3-540-27769-9

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