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A Relational Query Primitive for Constraint-Based Pattern Mining

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Constraint-Based Mining and Inductive Databases

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

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Abstract

As a step towards the design of an Inductive Database System, in this paper we present a primitive for constraint-based frequent pattern mining, which represents a careful trade-off between expressiveness and efficiency. Such primitive is a simple mechanism which takes a relational table in input and extracts from it all frequent patterns which satisfy a given set of user-defined constraints. Despite its simplicity, the proposed primitive is expressive enough to deal with a broad range of interesting constraint-based frequent pattern queries,using a comprehensive repertoire of constraints defined over SQL aggregates. Thanks to its simplicity, the proposed primitive is amenable to be smoothly embedded in a variety of data mining query languages and be efficiently executed, by the state-of-the-art optimization techniques based on pushing the various form of constraints by means of data reduction.

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Author information

Authors and Affiliations

  1. ISTI – CNR, Area della Ricerca di Pisa, Via Giuseppe Moruzzi, 1, 56124, Pisa, Italy

    Francesco Bonchi & Fosca Giannotti

  2. Dipartimento di Informatica, Via F. Buonarroti 2, 56127, Pisa, Italy

    Dino Pedreschi

Authors
  1. Francesco Bonchi
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  2. Fosca Giannotti
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  3. Dino Pedreschi
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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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Bonchi, F., Giannotti, F., Pedreschi, D. (2006). A Relational Query Primitive for Constraint-Based Pattern Mining. 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_2

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  • DOI: https://doi.org/10.1007/11615576_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-31331-1

  • Online ISBN: 978-3-540-31351-9

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