Hostname: page-component-f554764f5-qhdkw Total loading time: 0 Render date: 2025-04-18T17:16:26.137Z Has data issue: false hasContentIssue false
  • English
  • Français

A survey of Knowledge Discovery and Data Mining process models

Published online by Cambridge University Press:  07 July 2006

LUKASZ A. KURGAN  and
PETR MUSILEK
LUKASZ A. KURGAN
Affiliation:
Department of Electrical and Computer Engineering, University of Alberta, ECERF 2nd Floor, 9107 116 Street, Edmonton, Alberta, T6G 2V4, Canada; e-mail: [email protected]
PETR MUSILEK
Affiliation:
Department of Electrical and Computer Engineering, University of Alberta, ECERF 2nd Floor, 9107 116 Street, Edmonton, Alberta, T6G 2V4, Canada; e-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

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.

Type
Research Article
Information
The Knowledge Engineering Review , Volume 21 , Issue 1 , March 2006 , pp. 1 - 24
Copyright
© 2006 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable