PR
2011
13 years 3 months ago
2011
Increasingly large amount of multidimensional data are being generated on a daily basis in many applications. This leads to a strong demand for learning algorithms to extract usef...
IEEEVAST
2010
13 years 7 months ago
2010
Visualization of multi-dimensional data is challenging due to the number of complex correlations that may be present in the data but that are difficult to be visually identified. ...
DATESO
2009
13 years 10 months ago
2009
Indexing methods for efficient processing of multidimensional data are very requested in many fields, like geographical information systems, drawing documentations etc. Well-known ...
SEDE
2010
13 years 10 months ago
2010
New emerging scientific applications in geosciences, sensor and spatio-temporal domains require adaptive analysis frameworks that can handle large datasets with multiple dimension...
TVCG
2008
14 years 9 days ago
2008
Scatterplots remain one of the most popular and widely-used visual representations for multidimensional data due to their simplicity, familiarity and visual clarity, even if they l...
JDWM
2007
14 years 10 days ago
2007
Comprehensive data analysis has become indispensable in a variety of domains. OLAP (On-Line Analytical Processing) systems tend to perform poorly or even fail when applied to comp...
JDWM
2006
14 years 12 days ago
2006
Navigating through multidimensional data cubes is a nontrivial task. Although On-Line Analytical Processing (OLAP) provides the capability to view multidimensional data through ro...
IJCSA
2006
14 years 13 days ago
2006
Approaches to indexing and searching feature vectors are an indispensable factor to support similarity search effectively and efficiently. Such feature vectors extracted from real...
VDA
2010
14 years 2 months ago
2010
Spatialization is a special kind of visualization that projects multidimensional data into low-dimensional representational spaces by making use of spatial metaphors. Spatializati...
WAIM
2000
Springer
14 years 4 months ago
2000
Springer
Online Analytical Processing (OLAP) data is frequently organized in the form of multidimensional data cubes each of which is used to examine a set of data values, called measures, ...