Article ID: | iaor20021013 |
Country: | Netherlands |
Volume: | 40 |
Issue: | 4 |
Start Page Number: | 361 |
End Page Number: | 377 |
Publication Date: | Sep 2001 |
Journal: | Computers & Industrial Engineering |
Authors: | Kamrani Ali, Rong Wang, Gonzalez Ricardo |
Keywords: | statistics: empirical, datamining |
Data mining is a process that uses available technology to bridge the gap between data and logical decision making. The terminology itself provides a promising view of a systematic data manipulation for extracting useful information and knowledge from the high volume of data. Numerous techniques are developed to fulfill this goal. Implement data mining in an organization would impact every aspect and requires both hardware and software development. This paper outlines a series of discussions and description for data mining and its methodology. First, the definition of data mining along with the purposes and growing needs for such a technology is presented. A six-step methodology for data mining is then presented. Finally, steps from the methodology are applied in a case study to develop a GA-based system for intelligent knowledge discovery for machine diagnosis.