Title
Lossless Representation of Graphs using Distributions
Abstract
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.
Year
Venue
Keywords
2007
Clinical Orthopaedics and Related Research
graph representation,complete graph,pattern recognition
Field
DocType
Volume
Discrete mathematics,Combinatorics,Indifference graph,Graph isomorphism,Chordal graph,Cograph,Graph product,Pathwidth,1-planar graph,Mathematics,Maximal independent set
Journal
abs/0710.1
Citations 
PageRank 
References 
1
0.39
22
Authors
2
Name
Order
Citations
PageRank
Mireille Boutin116022.68
Gregor Kemper27011.53