Principles of Green Data Mining

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Schneider, J., Basalla, M., & Seidel, S. (2019). Principles of Green Data Mining. Paper presented at the Hawaii International Conference on System Sciences (HICSS), Hawaii, USA. (VHB_3: C)


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This paper develops a set of principles for green data mining, related to the key stages of business understanding, data understanding, data preparation, modeling, evaluation, and deployment. The principles are grounded in a review of the Cross Industry Standard Process for Data mining (CRISP-DM) model and relevant literature on data mining methods and Green IT. We describe how data scientists can contribute to designing environmentally friendly data mining processes, for instance, by using green energy, choosing between make-or-buy, exploiting approaches to data reduction based on business understanding or pure statistics, or choosing energy friendly models.



  • Institut für Wirtschaftsinformatik
  • Hilti Lehrstuhl für Business Process Management
  • Lehrstuhl für Informationssysteme und Innovation

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