Shortest path discovery of complex networks. Fekete, A., Vattay, G., & Posfai, M. abstract bibtex In this Letter we present an analytic study of sampled networks in the case of some important shortest-path sampling models. We present analytic formulas for the probability of edge discovery in the case of an evolving and a static network model. We also show that the number of discovered edges in a finite network scales much more slowly than predicted by earlier mean field models. Finally, we calculate the degree distribution of sampled networks, and we demonstrate that they are analogous to a destroyed network obtained by randomly re moving edges from the original network
@article{Fekete,
abstract = {In this Letter we present an analytic study of sampled networks in the case of some important shortest-path sampling models. We present analytic formulas for the probability of edge discovery in the case of an evolving and a static network model. We also show that the number of discovered edges in a finite network scales much more slowly than predicted by earlier mean field models. Finally, we calculate the degree distribution of sampled networks, and we demonstrate that they are analogous to a destroyed network obtained by randomly re moving edges from the original network},
archivePrefix = {arXiv},
arxivId = {arXiv:0810.1428v2},
author = {Fekete, Attila and Vattay, Gabor and Posfai, Marton},
eprint = {arXiv:0810.1428v2},
file = {:home/ecem/Dropbox/mendeley\_sampling\_references/Fekete, Vattay, Posfai/Unknown\_Fekete, Vattay, Posfai\_Shortest path discovery of complex networks.pdf:pdf},
pages = {1--10},
title = {{Shortest path discovery of complex networks}}
}
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