The Knowledge Engineering Review

Table of Contents - 2006 - Volume 21, Issue 01  

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A survey of Knowledge Discovery and Data Mining process models

LUKASZ A.  KURGAN a1 and PETR  MUSILEK a2
a1 Department of Electrical and Computer Engineering, University of Alberta, ECERF 2nd Floor, 9107 116 Street, Edmonton, Alberta, T6G 2V4, Canada; e-mail: lkurgan@ece.ualberta.ca
a2 Department of Electrical and Computer Engineering, University of Alberta, ECERF 2nd Floor, 9107 116 Street, Edmonton, Alberta, T6G 2V4, Canada; e-mail: musilek@ece.ualberta.ca

Article author query
kurgan l   [Google Scholar] 
musilek p   [Google Scholar] 
 

Abstract

Knowledge Discovery and Data Mining is a very dynamic research and development area that is reaching maturity. As such, it requires stable and well-defined foundations, which are well understood and popularized throughout the community. This survey presents a historical overview, description and future directions concerning a standard for a Knowledge Discovery and Data Mining process model. It presents a motivation for use and a comprehensive comparison of several leading process models, and discusses their applications to both academic and industrial problems. The main goal of this review is the consolidation of the research in this area. The survey also proposes to enhance existing models by embedding other current standards to enable automation and interoperability of the entire process.