Inferring Probability Distributions of Graph Size and Node Degree from Stochastic Graph Grammars

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Summary

It is shown that a stochastic graph grammar can be used to efficiently compute the probability mass functions of the number of nodes, thenumber of edges, and the degree of a node selected uniformly at random from a graph sampled from the distribution defined by the graph grammar.

Type
article
Published
2010-04-29
Cited by
1
References
21
Access
Open access

Keywords

Computer science, Rule-based machine translation, Graph, Graph property, Random graph

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