Title : 
Visualizing High Dimensional Datasets Using Partiview
         
        
            Author : 
Surendran, Dinoj ; Levy, Stuart
         
        
            Author_Institution : 
University of Chicago
         
        
        
        
            Abstract : 
A standard method of visualizing high-dimensional data is reducing its dimensionality to two or three using some algorithm, and then creating a scatterplot with data represented by labelled and/or colored dots. Two problems with this approach are (1) dots do not represent data well, (2) reducing to just three dimensions does not make full use of several dimensionality-reduction algorithms. We demonstrate how Partiview can be used to solve these problems, in the context of handwriting recognition and image retrieval.
         
        
            Keywords : 
dimensionality reduction; glyphs; high dimensional data visualization; image retrieval; information visualization; optical character recognition; Bioinformatics; Computer graphics; Data visualization; Face recognition; Frequency; Genomics; Hardware; Humans; Image retrieval; Information retrieval;
         
        
        
        
            Conference_Titel : 
Information Visualization, 2004. INFOVIS 2004. IEEE Symposium on
         
        
        
            Print_ISBN : 
0-7803-8779-3
         
        
        
            DOI : 
10.1109/INFVIS.2004.76