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arxiv: 0710.1870 · v1 · submitted 2007-10-09 · 🧮 math.CO · cs.CV

Lossless Representation of Graphs using Distributions

classification 🧮 math.CO cs.CV
keywords graphsweightsdistributionsdetermineddistributiongraphisomorphismlarge
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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.

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