Name
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. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/INFOVIS.2004.76 | InfoVis |
Keywords | Field | DocType |
high-dimensional data,dimensionality-reduction algorithm,visualizing high dimensional,handwriting recognition,image retrieval,full use,standard method,dimensionality reduction,optical character recognition,high dimensional data,three dimensions,information visualization,glyphs,visualization | Glyph,Data mining,Colored,Dimensionality reduction,Information visualization,Computer science,Optical character recognition,Image retrieval,Handwriting recognition,Curse of dimensionality | Conference |
ISBN | Citations | PageRank |
0-7803-8779-3 | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dinoj Surendran | 1 | 20 | 2.97 |
| Stuart Levy | 2 | 17 | 2.23 |