%0 Conference Proceedings
%4 sid.inpe.br/banon/2004/08.21.12.06
%2 sid.inpe.br/banon/2004/08.21.12.06.37
%@doi 10.1109/SIBGRA.2004.1352979
%T Viz3D: Effective exploratory visualization of large multidimensional data sets.
%D 2004
%A Artero, Almir Olivette,
%A Oliveira, Maria Cristina Ferreira,
%@affiliation Instituto de Ciências Matemáticas e Computação
%@affiliation Universidade de São Paulo
%@affiliation Caixa Postal 668, 13.560-970, São Carlos SP, Brasil,
%E Araújo, Arnaldo de Albuquerque,
%E Comba, João Luiz Dihl,
%E Navazo, Isabel,
%E Sousa, Antônio Augusto de,
%B Brazilian Symposium on Computer Graphics and Image Processing, 17 (SIBGRAPI) - Ibero-American Symposium on Computer Graphics, 2 (SIACG)
%C Curitiba, PR, Brazil
%8 17-20 Oct. 2004
%I IEEE Computer Society
%J Los Alamitos
%S Proceedings
%K information visualization, visual data mining, clustering.
%X 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.
%@language en
%3 4418_Artero_Oliveira.pdf