Paper Info
Title
Viz3D: effective exploratory visualization of large multidimensional data sets
Abstract
We propose a multidimensional visualization technique, named Viz3D, that creates a 3D representation of n-dimensional data that may be interactively manipulated by users to handle visual cluttering and object occlusion. The projection performed in Viz3D is comparable in quality with the 3D projections obtained with well-known dimensionality reduction techniques, at a lower complexity cost. While a 3D projection conveys more information, giving the user more control of the visual representation and an additional dimension, as compared to 2D, visual cluttering and object occlusion are still a problem in handling large multidimensional data sets. To produce more effective visualizations, two strategies are introduced. Dimensionality is handled with a similarity clustering of attributes prior to projection. Data set size is handled with a new strategy of visualizing data densities, rather than individual data records. Both the direct and density Viz3D visualizations provide the basis for a user driven visual clustering approach applicable to high-dimensional data sets that is very simple, intuitive and effective.
Year
DOI
Venue
2004
10.1109/SIBGRA.2004.1352979
SIBGRAPI
Keywords
Field
DocType
data visualisation,pattern clustering,very large databases,3D representation,Viz3D,data densities,data set size,dimensionality,large multidimensional data sets,multidimensional visualization technique,n-dimensional data,object occlusion,similarity clustering,user driven visual clustering,visual cluttering,visual representation
Data mining,Data visualization,Data set,Dimensionality reduction,Information visualization,Visualization,Computer science,Curse of dimensionality,3D projection,Cluster analysis
Conference
ISSN
ISBN
Citations 
1530-1834
0-7695-2227-0
12
PageRank 
References 
Authors
0.82
11
2
Name
Order
Citations
PageRank
Almir Olivette Artero1301.65
Maria Cristina F. De Oliveira223813.18