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Data Mining: Foundations and Practice pp 165–178Cite as

Towards a Methodology for Data Mining Project Development: The Importance of Abstraction

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 118))

Summary

Standards such as CRISP-DM, SEMMA, PMML, are making data mining processes easier. Nevertheless, up to date, projects are being developed more as an art than as a science making it difficult to understand, evaluate and compare results as there is no standard methodology. In this chapter, we make a proposal for such a methodology based on RUP and CRISP-DM and concentrate on the project conception phase for determining a feasible project plan.

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Author information

Authors and Affiliations

  1. Universidad Politecnica de Madrid, Madrid, Spain

    P. González-Aranda, E. Menasalvas, Carlos Ruiz & J. Segovia

  2. Universidad del Valle., Cali, Colombia

    S. Millán

Authors
  1. P. González-Aranda
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  2. E. Menasalvas
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  3. S. Millán
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  4. Carlos Ruiz
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  5. J. Segovia
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Editor information

Editors and Affiliations

  1. Department of Computer Science, San Jose State University, San Jose, CA, 95192, USA

    Tsau Young Lin

  2. Department of Computer Science and Information Systems, Kennesaw State University, Building 11, Room 3060 1000 Chastain Road, Kennesaw, GA, 30144, USA

    Ying Xie

  3. Department of Computer Science, The University at Stony Brook, Stony Brook, New York, 11794-4400, USA

    Anita Wasilewska

  4. Institute of Information Science, Academia Sinica, No 128, Academia Road, Section 2 Nankang, Taipei, 11529, Taiwan

    Churn-Jung Liau

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© 2008 Springer-Verlag Berlin Heidelberg

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González-Aranda, P., Menasalvas, E., Millán, S., Ruiz, C., Segovia, J. (2008). Towards a Methodology for Data Mining Project Development: The Importance of Abstraction. In: Lin, T.Y., Xie, Y., Wasilewska, A., Liau, CJ. (eds) Data Mining: Foundations and Practice. Studies in Computational Intelligence, vol 118. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78488-3_10

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  • DOI: https://doi.org/10.1007/978-3-540-78488-3_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-78487-6

  • Online ISBN: 978-3-540-78488-3

  • eBook Packages: EngineeringEngineering (R0)

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