Lossless Representation of Graphs using Distributions
| dc.creator | Boutin, Mireille | |
| dc.creator | Kemper, Gregor | |
| dc.date | 2007-10-09 | |
| dc.date.accessioned | 2026-07-07T08:35:19Z | |
| dc.date.available | 2026-07-07T08:35:19Z | |
| dc.description | We consider complete graphs with edge weights and/or node weights taking values in some set. In the first part of this paper, we show that a large number of graphs are completely determined, up to isomorphism, by the distribution of their sub-triangles. In the second part, we propose graph representations in terms of one-dimensional distributions (e.g., distribution of the node weights, sum of adjacent weights, etc.). For the case when the weights of the graph are real-valued vectors, we show that all graphs, except for a set of measure zero, are uniquely determined, up to isomorphism, from these distributions. The motivating application for this paper is the problem of browsing through large sets of graphs. | |
| dc.description | 19 pages | |
| dc.identifier | https://arxiv.org/abs/0710.1870 | |
| dc.identifier | http://arxiv.org/abs/0710.1870 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/139710 | |
| dc.subject | Combinatorics | |
| dc.subject | Computer Vision and Pattern Recognition | |
| dc.title | Lossless Representation of Graphs using Distributions | |
| dc.type | text |