A Systematic Literature Review on Applying CRISP-DM Process Model

By Christoph Schröer, Felix Kruse, J. Gómez. CENTERIS/ProjMAN/HCist, 2020

564 citations recorded by the source corpus.

Abstract 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.

Subfields: Management Information Systems, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/5a124cd7063f5d4f98e22ef0276f193e9eb159aa