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 ...
Abstract. Visual data
ow environments are ideally suited for modeling digital signal processing (DSP) systems, as many DSP algorithms are most naturally specied by signal
ow gra...
James Hwang, Brent Milne, Nabeel Shirazi, Jeffrey ...
Many data sets exist that contain both geospatial and temporal elements. Within such data sets, it can be difficult to determine how the data have changed over spatial and tempor...
Orland Hoeber, Garnett Carl Wilson, Simon Harding,...
Background: Improvements in technology have been accompanied by the generation of large amounts of complex data. This same technology must be harnessed effectively if the knowledg...
Background: Microarray-based comparative genome hybridization experiments generate data that can be mapped onto the genome. These data are interpreted more easily when represented...
Ihab A. B. Awad, Christian A. Rees, Tina Hernandez...