A survey of Knowledge Discovery and Data Mining process models

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.

Using Decision Trees for Estimating Mode Choice of Trips in Buca-Izmir

“…Data mining techniques can be applied with several knowledge process models (Kurgan & Musilek, 2006;Cios and et al, 2007) Cross Industry Standard Process for Data Mining (CRISP-DM) which is a knowledge discovery and data mining process, is one of these models. This process model is jointly developed by cooperations DaimlerChrysler AG, SPSS, NCR, and OHRA (CRISP-DM, 2000).…”

Data Mining Applications: Promise and Challenges

“…Today, a number of process models exists which aims to provide structure, control and standard methodology in applying data mining (Fayyad et al,1996a;Cabena et al, 1998;Anand & Buchner, 1998;Chapman et al 2000;Cios et al, 2000;Han & Kamber, 2001;Adriaans & Zantinge, 1996;Berry & Linoff, 1997;SAS Institute, 2003;Edelstein , 1998;Klösgen & Zytkow, 2002 ;Haglin et al 2005). These process models are also known as Knowledge Discovery and Data Mining (KDDM) process models (Kurgan & Musilek, 2006). The KDDM process models outline the fundamental set of steps (typically executed iteratively with loopbacks) required in data mining applications covering the entire lifecycle in applying data mining from the initial goal determination to the final deployment and maintenance of the discovered knowledge.…”

“…The basic structure for KDDM process models was initially proposed by Fayyad et al (Fayyad et al,1996a, Fayyad et al,1996b) (popularly known as the "KDD Process") with other models proposed later. A survey and comparison of prominent KDDM process models are presented in (Kurgan & Musilek, 2006). The KDDM process models outline the fundamental set of steps (typically executed iteratively with loopbacks) required in data mining applications.…”

“…The different KDDM process models are similar except mainly for terminology, orientation towards research vs. industry contexts and emphasis on different steps. In (Kurgan & Musilek, 2006), the prominent KDDM process models (Fayyad et al,1996a;Cabena et al, 1998;Chapman et al 2000;Anand & Buchner, 1998;Cios et al, 2000) are compared. Figure 2 illustrates a comparison table presented in (Kurgan & Musilek, 2006) mapping the different steps in the prominent process models.…”

“…It is evident that all process models follow more-or-less a similar set of steps. Some of the similaritites outlined in (Kurgan & Musilek, 2006) are given below:…”