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CRISP-DM is the de-facto standard and an industry-independent process model for applying data mining projects. Twenty years after its release in 2000, we would like to provide a systematic literature review of recent studies published in IEEE, ScienceDirect and ACM about data mining use cases applying CRISP-DM. We give an overview of the research focus, current methodologies, best practices and possible gaps in conducting the six phases of CRISP-DM. The main findings are that CRISP-DM is still a de-factor standard in data mining, but there are challenges since the most studies do not foresee a deployment phase. The contribution of our paper is to identify best practices and process phases in which data mining analysts can be better supported. Further contribution is a template for structuring and releasing CRISP-DM studies.
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Christoph Schröer
Carl von Ossietzky Universität Oldenburg
Felix Kruse
Carl von Ossietzky Universität Oldenburg
Jorge Marx Gómez
Carl von Ossietzky Universität Oldenburg
Procedia Computer Science
Carl von Ossietzky Universität Oldenburg
Volkswagen Group (Germany)
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Schröer et al. (Fri,) studied this question.
synapsesocial.com/papers/6a03793f5ecd4fc6d488c924 — DOI: https://doi.org/10.1016/j.procs.2021.01.199