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| Author(s) |
Brandes, U., Pich, C. |
| Title |
Eigensolver methods for progressive multidimensional scaling of large data |
| Abstract |
We present a novel sampling-based approximation technique
for classical multidimensional scaling that yields an extremely fast layout
algorithm suitable even for very large graphs. It produces layouts that
compare favorably with other methods for drawing large graphs, and it
is among the fastest methods available. In addition, our approach allows
for progressive computation, i.e. a rough approximation of the layout can
be produced even faster, and then be refined until satisfaction. |
| Download |
BrPi06.pdf |
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