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Inductive Databases and Constraint-Based Data Mining

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Formal Concept Analysis (ICFCA 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6628))

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Abstract

We briefly introduce the notion of an inductive database, explain its relation to constraint-based data mining, and illustrate it on an example. We then discuss constraints and constraint-based data mining in more detail. We further give an overview of recent developments in the area, focusing on those made within the IQ project and presented in a recent volume with the same title as this paper, edited by the author, Bart Goethals and Panče Panov, and published by Springer.

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Authors and Affiliations

  1. Jožef Stefan Institute, Jamova 39, 1000, Ljubljana, Slovenia

    Sašo Džeroski

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  1. Sašo Džeroski
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Editors and Affiliations

  1. Département d’Informatique, Université du Québec à Montréal, Succ. Centre-Ville, Montréal, C.P.8888, H3C 3P8, Québec, Canada

    Petko Valtchev

  2. Universität Kassel, Fachgebiet Wissensverarbeitung, Wilhelmshöher Allee 73, 34121, Kassel, Germany

    Robert Jäschke

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Džeroski, S. (2011). Inductive Databases and Constraint-Based Data Mining. In: Valtchev, P., Jäschke, R. (eds) Formal Concept Analysis. ICFCA 2011. Lecture Notes in Computer Science(), vol 6628. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20514-9_1

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  • DOI: https://doi.org/10.1007/978-3-642-20514-9_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20513-2

  • Online ISBN: 978-3-642-20514-9

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