# Kronecker Graphs: An Approach to Modeling Networks

@article{Leskovec2010KroneckerGA, title={Kronecker Graphs: An Approach to Modeling Networks}, author={Jure Leskovec and Deepayan Chakrabarti and Jon M. Kleinberg and Christos Faloutsos and Zoubin Ghahramani}, journal={Journal of Machine Learning Research}, year={2010}, volume={11}, pages={985-1042} }

- Published in Journal of Machine Learning Research 2010
DOI:10.1145/1756006.1756039

How can we generate realistic networks? In addition, how can we do so with a mathematically tractable model that allows for rigorous analysis of networ k properties? Real networks exhibit a long list of surprising properties: Heavy tails for the ina nd out-degree distribution; heavy tails for the eigenvalues and eigenvectors; small diameters; and de sification and shrinking diameters over time. The present network models and generators either fail to match several of the above properties, are… CONTINUE READING

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