Sublinear Algorithms for Local Graph Centrality Estimation

@article{Bressan2018SublinearAF,
  title={Sublinear Algorithms for Local Graph Centrality Estimation},
  author={Marco Bressan and Enoch Peserico and Luca Pretto},
  journal={2018 IEEE 59th Annual Symposium on Foundations of Computer Science (FOCS)},
  year={2018},
  pages={709-718}
}
  • M. Bressan, E. Peserico, L. Pretto
  • Published 7 April 2014
  • Computer Science, Mathematics
  • 2018 IEEE 59th Annual Symposium on Foundations of Computer Science (FOCS)
We study the complexity of local graph centrality estimation, with the goal of approximating the centrality score of a given target node while exploring only a sublinear number of nodes/arcs of the graph and performing a sublinear number of elementary operations. We develop a technique, that we apply to the PageRank and Heat Kernel centralities, for building a low-variance score estimator through a local exploration of the graph. We obtain an algorithm that, given any node in any graph of m… 

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