TY - GEN
T1 - An enhanced data mining life cycle
AU - Hofmann, Markus
AU - Tierney, Brendan
PY - 2009
Y1 - 2009
N2 - Data mining projects are complex and can have a high failure rate. In order to improve project management and success rates of such projects a life cycle is vital to the overall success of the project. This paper reports on a research project that was concerned with the life cycle development for data mining projects, its team members and their role. The paper provides a detailed view of the design and development of the data mining life cycle called DMLC. The life cycle aims to support all members of data mining project teams as well as IT managers and academic researchers and may improve project success rates and strategic decision support. An extensive analysis of eight life cycles leads to a list of advantages, disadvantages, and characteristics of the life cycles. This is extended and generates a conglomerate of several guidelines which serve as the foundation for the development of a new generic data mining life cycle. A detailed study of the human resources involved in a data mining project enhances the DMLC.
AB - Data mining projects are complex and can have a high failure rate. In order to improve project management and success rates of such projects a life cycle is vital to the overall success of the project. This paper reports on a research project that was concerned with the life cycle development for data mining projects, its team members and their role. The paper provides a detailed view of the design and development of the data mining life cycle called DMLC. The life cycle aims to support all members of data mining project teams as well as IT managers and academic researchers and may improve project success rates and strategic decision support. An extensive analysis of eight life cycles leads to a list of advantages, disadvantages, and characteristics of the life cycles. This is extended and generates a conglomerate of several guidelines which serve as the foundation for the development of a new generic data mining life cycle. A detailed study of the human resources involved in a data mining project enhances the DMLC.
UR - http://www.scopus.com/inward/record.url?scp=67650501908&partnerID=8YFLogxK
U2 - 10.1109/CIDM.2009.4938637
DO - 10.1109/CIDM.2009.4938637
M3 - Conference contribution
AN - SCOPUS:67650501908
SN - 9781424427659
T3 - 2009 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009 - Proceedings
SP - 109
EP - 117
BT - 2009 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009 - Proceedings
T2 - 2009 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2009
Y2 - 30 March 2009 through 2 April 2009
ER -