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 ...
ICA (independent component analysis) is a new, simple and powerful idea for analyzing multi-variant data. One of the successful applications is neurobiological data analysis such ...
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, Stefan Grundlach, Hans-Peter Kriegel...
Many data sets are incomplete. For correct analysis of such data, one can either use algorithms that are designed to handle missing data or use imputation. Imputation has the bene...
Although a huge amount of remote sensing data has been provided by Earth observation satellites, few data manipulation techniques and information extraction in large data sets hav...
Thales Sehn Korting, Leila Maria Garcia Fonseca, M...