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The Smaller the Better: Comparison of Two Approaches for Sales Rate Prediction

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Advances in Intelligent Data Analysis V (IDA 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2810))

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Abstract

We describe a system to predict the daily sales rates of newspapers. We deduce a mathematical modeling and its implementation, a data cleaning approach, and a way to augment the training sets using similar time series. The results are compared with a neural prediction system currently in use.

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References

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Author information

Authors and Affiliations

  1. Lehrstuhl Informatik I, Universität Dortmund, 44221, Dortmund, Germany

    Martin Lauer & Martin Riedmiller

  2. quantiom bioinformatics, Ringstrasse 61, 76356, Weingarten, Germany

    Thomas Ragg

  3. Axel-Springer-Verlag, 20355, Hamburg, Germany

    Walter Baum & Michael Wigbers

Authors
  1. Martin Lauer
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  2. Martin Riedmiller
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  3. Thomas Ragg
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  4. Walter Baum
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  5. Michael Wigbers
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Editor information

Editors and Affiliations

  1. Berkeley Initiative in Soft Computing (BISC), University of California at Berkeley, USA

    Michael R. Berthold

  2. Freie Universität Berlin, Garystr. 21, 14195, Berlin, Germany

    Hans-Joachim Lenz

  3. Department of Computer Science, University of Colorado, Boulder, Colorado, USA

    Elizabeth Bradley

  4. Otto-von-Guericke-University of Magdeburg, Germany

    Rudolf Kruse

  5. Department of Knowledge Processing and Language Engineering, University of Magdeburg, Universitätsplatz 2, 39106, Magdeburg, Germany

    Christian Borgelt

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© 2003 Springer-Verlag Berlin Heidelberg

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Lauer, M., Riedmiller, M., Ragg, T., Baum, W., Wigbers, M. (2003). The Smaller the Better: Comparison of Two Approaches for Sales Rate Prediction. In: R. Berthold, M., Lenz, HJ., Bradley, E., Kruse, R., Borgelt, C. (eds) Advances in Intelligent Data Analysis V. IDA 2003. Lecture Notes in Computer Science, vol 2810. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45231-7_42

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  • DOI: https://doi.org/10.1007/978-3-540-45231-7_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40813-0

  • Online ISBN: 978-3-540-45231-7

  • eBook Packages: Springer Book Archive

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