Eigensolver Methods for Progressive Multidimensional Scaling of Large Data
| Type of Publication: | Contribution to a conference collection |
| URI (citable link): | http://nbn-resolving.de/urn:nbn:de:bsz:352-opus-73423 |
| Author: | Brandes, Ulrik; Pich, Christian |
| Year of publication: | 2007 |
| Published in: | Graph Drawing / Kaufmann, Michael; Wagner, Dorothea (ed.). - Berlin, Heidelberg : Springer Berlin Heidelberg, 2007. - (Lecture Notes in Computer Science). - pp. 42-53. - ISBN 978-3-540-70903-9 |
| DOI (citable link): | https://dx.doi.org/10.1007/978-3-540-70904-6_6 |
| Summary: |
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.
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| Subject (DDC): | 004 Computer Science |
| Link to License: | Attribution-NonCommercial-NoDerivs 2.0 Generic |
| Bibliography of Konstanz: | Yes |
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BRANDES, Ulrik, Christian PICH, 2007. Eigensolver Methods for Progressive Multidimensional Scaling of Large Data. In: KAUFMANN, Michael, ed., Dorothea WAGNER, ed.. Graph Drawing. Berlin, Heidelberg:Springer Berlin Heidelberg, pp. 42-53. ISBN 978-3-540-70903-9. Available under: doi: 10.1007/978-3-540-70904-6_6
@inproceedings{Brandes2007Eigen-5741, title={Eigensolver Methods for Progressive Multidimensional Scaling of Large Data}, year={2007}, doi={10.1007/978-3-540-70904-6_6}, isbn={978-3-540-70903-9}, address={Berlin, Heidelberg}, publisher={Springer Berlin Heidelberg}, series={Lecture Notes in Computer Science}, booktitle={Graph Drawing}, pages={42--53}, editor={Kaufmann, Michael and Wagner, Dorothea}, author={Brandes, Ulrik and Pich, Christian} }
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