An engineering approach to data mining projects

  • Authors:

  • Óscar Marbán;Gonzalo Mariscal;Ernestina Menasalvas;Javier Segovia

  • Affiliations:

  • Facultad de Informática, Universidad Politécnica de Madrid, Madrid, Spain;Universidad Europea de Madrid;Facultad de Informática, Universidad Politécnica de Madrid, Madrid, Spain;Facultad de Informática, Universidad Politécnica de Madrid, Madrid, Spain

  • Venue:
  • IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
  • Year:
  • 2007

  • Review:

    The Knowledge Engineering Review

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Abstract

Both the number and complexity of Data Mining projects has increased in late years. Unfortunately, nowadays there isn't a formal process model for this kind of projects, or existing approaches are not right or complete enough. In some sense, present situation is comparable to that in software that led to 'software crisis' in latest 60's. Software Engineering matured based on process models and methodologies. Data Mining's evolution is being parallel to that in Software Engineering. The research work described in this paper proposes a ProcessModel for Data Mining Projects based on the study of current Software Engineering Process Models (IEEE Std 1074 and ISO 12207) and the most used Data Mining Methodology CRISP-DM (considered as a "facto" standard) as basic references.