Authors: Georg Peters, Richard Weber
Addresses: Department of Computer Science and Mathematics, University of Applied Sciences – Munchen, Lothstrasse 34, 80335 Munich, Germany. ' Department of Industrial Engineering, University of Chile, Republica 701, Santiago, Chile
Abstract: Many real life applications are characterised by changing data structures. For example, the buying patterns of retail customers may change due to changing economical parameters (increasing oil prices motivate to buy smaller cars) or a technological break-through (replacement of analogue by digital cameras). In such dynamic environments the parameters obtained in data mining projects need to be updated to adequately describe the actual real life situation. Dynamic data mining addresses such situations. It has been applied successfully in many projects, like in traffic data analysis. In our paper, we apply the concepts of dynamic data mining to rough k-means.
Keywords: dynamic data mining; clustering algorithms; moving clusters; rough sets; data structures.
International Journal of Intelligent Defence Support Systems, 2009 Vol.2 No.2, pp.105 - 119
Available online: 21 Sep 2009 *Full-text access for editors Access for subscribers Purchase this article Comment on this article