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SQL-Based KDD with Infobright’s RDBMS: Attributes, Reducts, Trees

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Rough Sets and Intelligent Systems Paradigms

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8537))

Abstract

We present a framework for KDD process implemented using SQL procedures, consisting of constructing new attributes, finding rough set-based reducts and inducing decision trees. We focus particularly on attribute reduction, which is important especially for high-dimensional data sets. The main technical contribution of this paper is a complete framework for calculating short reducts using SQL queries on data stored in a relational form, without a need of any external tools generating or modifying their syntax. A case study of large real-world data is presented. The paper also recalls some other examples of SQL-based data mining implementations. The experimental results are based on the usage of Infobright’s analytic RDBMS, whose performance characteristics perfectly fit the requirements of presented algorithms.

The second author was partly supported by Polish National Science Centre (NCN) grants DEC-2011/01/B/ST6/03867 and DEC-2012/05/B/ST6/03215, and by National Centre for Research and Development (NCBiR) grant SP/I/1/77065/10 by the strategic scientific research and experimental development program: “Interdisciplinary System for Interactive Scientific and Scientific-Technical Information”.

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Author information

Authors and Affiliations

  1. Infobright Inc., ul. Krzywickiego 34, lok. 219, 02-078, Warsaw, Poland

    Jakub Wróblewski

  2. Institute of Mathematics, University of Warsaw, ul. Banacha 2, 02-097, Warsaw, Poland

    Sebastian Stawicki

Authors
  1. Jakub Wróblewski
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  2. Sebastian Stawicki
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Editor information

Editors and Affiliations

  1. Institute of Computer Science, Warsaw University of Technology, Nowowiejska 15/19, 00-665, Warsaw, Poland

    Marzena Kryszkiewicz  & Zbigniew W. Raś  & 

  2. Department of Computer Science and Artificial Intelligence, University of Granada, Calle del Periodista Daniel Saucedo Aranda s/n, 18071, Granada, Spain

    Chris Cornelis

  3. DISCo, Università di Milano – Bicocca, Viale Sarca 336 – U14, 20126, Milano, Italy

    Davide Ciucci

  4. Dpt. de Matemáticas, University of Càdiz, Spain

    Jesús Medina-Moreno

  5. School of Computing and Information Systems, University of Tasmania, Japan

    Hiroshi Motoda

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Wróblewski, J., Stawicki, S. (2014). SQL-Based KDD with Infobright’s RDBMS: Attributes, Reducts, Trees. In: Kryszkiewicz, M., Cornelis, C., Ciucci, D., Medina-Moreno, J., Motoda, H., Raś, Z.W. (eds) Rough Sets and Intelligent Systems Paradigms. Lecture Notes in Computer Science(), vol 8537. Springer, Cham. https://doi.org/10.1007/978-3-319-08729-0_3

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  • DOI: https://doi.org/10.1007/978-3-319-08729-0_3

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08728-3

  • Online ISBN: 978-3-319-08729-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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