Intelligent cluster algorithms for changing data structures

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.