Knowledge Discovery in Data Science

被引：0
|
作者：
Grady, Nancy W. [1 ]
机构：
[1] Sci Applicat Int Corp, Cyber Cloud & Data Sci, Oak Ridge, TN 37830 USA
来源：
2016 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA) | 2016年
关键词：
data science; big data; knowledge discovery; KDD; KDDM; KDDS; data mining; analytics; analytics lifecycle; data lifecycle; PROCESS MODELS;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Cross-Industry Standard process model (CRISPDM) was developed in the late 90s by a consortium of industry participants to facilitate the end-to-end data mining process for Knowledge Discovery in Databases (KDD). While there have been efforts to better integrate with management and software development practices, there are no extensions to handle the new activities involved in using big data technologies. Data Science Edge (DSE) is an enhanced process model to accommodate big data technologies and data science activities. In recognition of the changes, the author promotes the use of a new term, Knowledge Discovery in Data Science (KDDS) as a call for the community to develop a new industry standard data science process model.
引用
收藏
页码：1603 / 1608
页数：6
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