Spatial data mining is a process used to discover interesting but not explicitly available, highly usable patterns embedded in both spatial and nonspatial data, which are possibly ...
Large amount of available information does not necessarily imply that induction algorithms must use all this information. Samples often provide the same accuracy with less computat...
There is a need to develop methods to automatically incorporate prior knowledge to support the prediction and validation of novel functional associations. One such important sourc...
Francisco Azuaje, Haiying Wang, Huiru Zheng, Olivi...
Today, there is a huge amount of data gathered about the Earth, not only from new spatial information systems, but also from new and more sophisticated data collection technologie...
Frederico T. Fonseca, Max J. Egenhofer, Peggy Agou...
Abstract: Spatial data mining algorithms heavily depend on the efficient processing of neighborhood relations since the neighbors of many objects have to be investigated in a singl...
Martin Ester, Alexander Frommelt, Hans-Peter Krieg...