The degree sequence of a scale-free random graph process
Random Structures & Algorithms
The boost graph library: user guide and reference manual
The boost graph library: user guide and reference manual
Modeling interactome: scale-free or geometric?
Bioinformatics
Graph-based text classification: learn from your neighbors
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
A survey of models of the web graph
CAAN'04 Proceedings of the First international conference on Combinatorial and Algorithmic Aspects of Networking
Streaming algorithms for k-core decomposition
Proceedings of the VLDB Endowment
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Generative models are often used in modeling real world graphs such as the Web graph in order to better understand the processes through which these graphs are formed. In order to determine if a graph might have been generated by a given model one must compare the features of that graph with those generated by the model. We introduce the concept of a hierarchical degree core tree as a novel way of summarizing the structure of massive graphs. The degree core of level kis the unique subgraph of minimal degree k. Hierarchical degree core trees are representations of the subgraph relationships between the components of the degree core of the graph, ranging over all possible values of k. We extract features related to the graph's local structure from these hierarchical trees. Using these features, we compare four real world graphs (a web graph, a patent citation graph, a co-authorship graph and an email graph) against a number of generative models.