Viz3D: Effective exploratory visualization of large multidimensional data sets

Brazilian Symposium of Computer Graphic and Image Processing

Volumn , Issue , 2004, Pages 340-347

  Artero, Almir Olivette ^a   De Oliveira, Maria Cristina Ferreira ^a  

^a UNIVERSITY OF SÃO PAULO   (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

DATA ORGANIZATIONS; EXPLORATORY VISUALIZATIONS; MULTIDIMENSIONAL DATA SETS; VISUAL CLUSTERING;

COMPUTATIONAL COMPLEXITY; COMPUTER GRAPHICS; DATA ACQUISITION; FEEDBACK; LINEAR SYSTEMS; PATTERN RECOGNITION;

VISUALIZATION;

EID: 16244370671     PISSN: 15301834     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/SIBGRA.2004.1352979     Document Type: Conference Paper

References (18)

1. Aggarwal, C. A Human-Computer Cooperative System for Effective High Dimensional Clustering, Proc. ACM Int. Conf. Knowledge Discovery and Data Mining 2001, 221 -226.
2. Ankerst, M., Berchtold, S., Keim, D.A. Similarity Clustering of Dimensions for Enhanced Visualization of Multidimensional Data, Proc. IEEE Symp. Information Visualization 1998 52-60.
3. Card, S.K., Mackinlay, J.D., Shneiderman, B., Readings in Information Visualization, Using Vision to Think, Morgan Kaufmann, 1999.
4. Faloutsos, G, Lin, K. FastMap: A Fast Algorithm for Indexing, Data-mining and Visualization of Traditional and Multimedia Datasets. Proc. SIGMOD Conf. 1995, 163-174.
5. Grinstein, G.G., Huffman, P.E., Pickett, R.M. Benchmark Development for the Evaluation of Visualization for Data Mining. In: Information Visualization in Data Mining and Knowledge Discovery, Fayyad, U., Grinstein, G.G. (eds.), 2001.
6. Halkidi, M., Vazirgiannis, M., Batistakis, I. Clustering Validation Techniques, Intelligent Information Systems J., 17(2-3), 2001, 107-145.
7. Hinneburg, A., Keim, D.A. An Efficient Approach To Clustering in Large Multimedia Databases With Noise, Proc. Int. Conf. Knowledge Discovery and Data Mining 1998, 58-65.
8. Hinneburg, A., Keim, D.A., Wawryniuk, M. HD-Eye: Visual Mining of High-Dimensional Data, IEEE Computer Graphics and Applications, 1999, 22-31.
9. Hoffman, P.E. Table Visualizations: A Formal Model and its Applications. Doctoral Diss., Computer Science Dept., University of Massachusetts, Lowell, MA, 1999.
10. Inselberg, A. The Plane with Parallel Coordinates, The Visual Computer, Special Issue on Computational Geometry, 1, 1985, 69-92.
11. Kandogan, E. Visualizing Multi-Dimensional Clusters, Trends, and Outliers using Star Coordinates, Proc. ACM Int. Conf. Knowledge Discovery and Data Mining 2001, 107-116
12. Keim, D.A. Information Visualization and Visual Data Mining, IEEE Trans. Visualization and Computers Graphics, 8, 2002, 1-8.
13. Molina, L.C., Belanche, L., Nebot A., Feature Selection Algorithms: A Survey and Experimental Evaluation, Proc. IEEE Int. Conf. on Data Mining 2002, 306-313.
14. Oliveira, M.C.F., Levkowitz, H. From Visualization to Visual Data Mining: A Survey. IEEE Trans. Visualization and Computer Graphics, 9, 2003, 378-394.
15. Pearson, K. On Lines and Planes of Closest Fit to System of Points in Space, Philosophy Magazine, 6, 1901, 559-572.
16. Rodrigues Jr, J.F., Traina, A.J., Traina Jr, C., Frequency Plot and Relevance Plot to Enhance Visual Data Exploration. Proc. XVI Brazilian Symp. Computer Graphics and Image Processing, 2003, 117-124.
17. Wegman, E.J., Luo, Q. High Dimensional Clustering using Parallel Coordinates and the Grand Tour. Proc. Conf. German Classification Society, Freiburg, Germany, 1996.
18. Yang, J., Ward, M.O., Rundensteiner, E. A., Huang, S. Visual Hierarchical Dimension Reduction for Exploration of High Dimensional Datasets, VisSym 2003.