The collaborative approach is a natural way to enhance visualization and visual analytics methods. This paper continues our long-term efforts on enhancement of visualization and visual analytics methods. The major challenges in visualization of large n-D data in 2-D are not only in providing lossless visualization by using sophisticated computational methods, but also in supporting the most efficient and fast usage of abilities of users (agents) to analyze visualized information and to extract patterns visually. This paper describes a collaborative approach to support n-D data visualization based on new lossless n-D visualization methods that we propose. The second part of this work presented in a separate paper is focused on experimental r...
Visualization and interaction of multidimensional data always requires optimized solutions to integr...
Visual analysis has been used in many fields of research, such as health, biology, chemistry, social...
As the data and number of information sources keeps on mounting, the mining of necessary information...
The major challenges in visualization of large n-D data in 2-D are in supporting the most efficient ...
Often multidimensional data are visualized by splitting n-D data to a set of low dimensional data. W...
This book combines the advantages of high-dimensional data visualization and machine learning in the...
In the long run the cognitive algorithms intend to make super-intelligent machines and super-intelli...
Abstract: The exploration of multidimensional datasets of all possible sizes and dimensions is a lon...
Analysis and visualization of large data sets is time consuming and sometimes can be a very difficul...
Preserving all multidimensional data in two-dimensional visualization is a long-standing problem in ...
A new method for assisting with the visualization of large multidimensional datasets is proposed. We...
This thesis investigates new ways of using information visualization to support collaboration in co-...
From state-of-the-art visualization algorithms, we distill six working principles which are, by hypo...
Fundamental challenges and goals of the cognitive algorithms are moving super-intelligent machines a...
We propose a multidimensional visualization technique, named Viz3D, that creates a 3D representation...
Visualization and interaction of multidimensional data always requires optimized solutions to integr...
Visual analysis has been used in many fields of research, such as health, biology, chemistry, social...
As the data and number of information sources keeps on mounting, the mining of necessary information...
The major challenges in visualization of large n-D data in 2-D are in supporting the most efficient ...
Often multidimensional data are visualized by splitting n-D data to a set of low dimensional data. W...
This book combines the advantages of high-dimensional data visualization and machine learning in the...
In the long run the cognitive algorithms intend to make super-intelligent machines and super-intelli...
Abstract: The exploration of multidimensional datasets of all possible sizes and dimensions is a lon...
Analysis and visualization of large data sets is time consuming and sometimes can be a very difficul...
Preserving all multidimensional data in two-dimensional visualization is a long-standing problem in ...
A new method for assisting with the visualization of large multidimensional datasets is proposed. We...
This thesis investigates new ways of using information visualization to support collaboration in co-...
From state-of-the-art visualization algorithms, we distill six working principles which are, by hypo...
Fundamental challenges and goals of the cognitive algorithms are moving super-intelligent machines a...
We propose a multidimensional visualization technique, named Viz3D, that creates a 3D representation...
Visualization and interaction of multidimensional data always requires optimized solutions to integr...
Visual analysis has been used in many fields of research, such as health, biology, chemistry, social...
As the data and number of information sources keeps on mounting, the mining of necessary information...