A Systematic Literature Review on Applying CRISP-DM Process Model

被引:140
作者
Schroeer, Christoph [1 ,2 ]
Kruse, Felix [2 ]
Gomez, Jorge Marx [2 ]
机构
[1] Volkswagen Aktiengesell, Berliner Ring 2, D-38440 Wolfsburg, Germany
[2] Carl von Ossietzky Univ Oldenburg, Ammerlander Heerstr 114-118, D-26129 Oldenburg, Germany
来源
INTERNATIONAL CONFERENCE ON ENTERPRISE INFORMATION SYSTEMS / INTERNATIONAL CONFERENCE ON PROJECT MANAGEMENT / INTERNATIONAL CONFERENCE ON HEALTH AND SOCIAL CARE INFORMATION SYSTEMS AND TECHNOLOGIES 2020 (CENTERIS/PROJMAN/HCIST 2020) | 2021年 / 181卷
关键词
CRISP-DM; Literature Review; Data Mining; Process Methodology; Deployment;
D O I
10.1016/j.procs.2021.01.199
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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 defactor 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. (C) 2021 The Authors. Published by Elsevier B.V.
引用
收藏
页码:526 / 534
页数:9
相关论文
共 35 条
[1]  
Abbasi A, 2016, J ASSOC INF SYST, V17, pI
[2]  
Ahmed B, 2018, COMPUT SCI ELECTR, P11, DOI 10.1109/CEEC.2018.8674234
[3]  
Alexandre C, 2017, INT CONF COMPUT INTE, P88, DOI [10.1109/CICN.2017.21, 10.1109/CICN.2017.8319362]
[4]  
[Anonymous], 2015, Informationsmanagement
[5]  
[Anonymous], 2014, C4. 5: programs for machine learning
[6]  
Budi I., 2018 INT C APPL INF, P1
[7]  
Cato Patrick, 2016, THESIS U ERLANGEN NU
[8]  
Chapman P., 2000, CRISP-DM 1.0 - A step-by-step data mining guide
[9]  
Chiheb F, 2017, PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON MATHEMATICS AND INFORMATION TECHNOLOGY (ICMIT), P113, DOI 10.1109/MATHIT.2017.8259704
[10]  
Galleta D. T., 2019 IEEE 4 INT C CO, P115