Measurements at different time points and positions in large temporal or spatial databases requires effective and efficient data mining techniques. For several parallel measureme...
Ira Assent, Ralph Krieger, Boris Glavic, Thomas Se...
Many applications require the management of spatial data. Clustering large spatial databases is an important problem which tries to find the densely populated regions in the featu...
The clustering algorithm DBSCAN relies on a density-based notion of clusters and is designed to discover clusters of arbitrary shape as well as to distinguish noise. In this paper,...
Great e orts have been paid in the Intelligent Database Systems Research Lab for the research and development of e cient data mining methods and construction of on-line analytical...
Spatial data mining is the discovery of interesting relationships and characteristics that may exist implicitly in spatial databases. In this paper, we explore whether clustering ...