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A Survey on Condensed Representations for Frequent Sets

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Constraint-Based Mining and Inductive Databases

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3848))

Abstract

Solving inductive queries which have to return complete collections of patterns satisfying a given predicate has been studied extensively the last few years. The specific problem of frequent set mining from potentially huge boolean matrices has given rise to tens of efficient solvers. Frequent sets are indeed useful for many data mining tasks, including the popular association rule mining task but also feature construction, association-based classification, clustering, etc. The research in this area has been boosted by the fascinating concept of condensed representations w.r.t. frequency queries. Such representations can be used to support the discovery of every frequent set and its support without looking back at the data. Interestingly, the size of condensed representations can be several orders of magnitude smaller than the size of frequent set collections. Most of the proposals concern exact representations while it is also possible to consider approximated ones, i.e., to trade computational complexity with a bounded approximation on the computed support values. This paper surveys the core concepts used in the recent works on condensed representation for frequent sets.

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Author information

Authors and Affiliations

  1. University of Antwerp, Belgium

    Toon Calders

  2. INSA Lyon, LIRIS CNRS UMR 5205, France

    Christophe Rigotti & Jean-François Boulicaut

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  1. Toon Calders
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  2. Christophe Rigotti
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  3. Jean-François Boulicaut
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Editor information

Editors and Affiliations

  1. INSA-Lyon, LIRIS CNRS UMR5205, F-69621, Villeurbanne, France

    Jean-François Boulicaut

  2. Department of Computer Science, Katholieke Universiteit Leuven, Celestijnenlaan 200A, 3001, Heverlee, Belgium

    Luc De Raedt

  3. HIIT, Helsinki University of Technology and, University of Helsinki, Finland

    Heikki Mannila

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Calders, T., Rigotti, C., Boulicaut, JF. (2006). A Survey on Condensed Representations for Frequent Sets. In: Boulicaut, JF., De Raedt, L., Mannila, H. (eds) Constraint-Based Mining and Inductive Databases. Lecture Notes in Computer Science(), vol 3848. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11615576_4

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  • DOI: https://doi.org/10.1007/11615576_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-31331-1

  • Online ISBN: 978-3-540-31351-9

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