Inspired by empirical studies of networked systems such as the Internet,
social networks, and biological networks, researchers have in recent years
developed a variety of techniques and models to help us understand or predict
the behavior of these systems. Here we review developments in this field,
including such concepts as the small-world effect, degree distributions,
clustering, network correlations, random graph models, models of network growth
and preferential attachment, and dynamical processes taking place on networks.
%0 Generic
%1 citeulike:155
%A Newman, M. E. J.
%D 2003
%K algorithm clustering complex_systems folksonomy information kdubiq network retrieval scale_free_networks small socialnetwork summerschool theory web web_graph world
%T The structure and function of complex networks
%U http://arxiv.org/abs/cond-mat/0303516
%X Inspired by empirical studies of networked systems such as the Internet,
social networks, and biological networks, researchers have in recent years
developed a variety of techniques and models to help us understand or predict
the behavior of these systems. Here we review developments in this field,
including such concepts as the small-world effect, degree distributions,
clustering, network correlations, random graph models, models of network growth
and preferential attachment, and dynamical processes taking place on networks.
@misc{citeulike:155,
abstract = {Inspired by empirical studies of networked systems such as the Internet,
social networks, and biological networks, researchers have in recent years
developed a variety of techniques and models to help us understand or predict
the behavior of these systems. Here we review developments in this field,
including such concepts as the small-world effect, degree distributions,
clustering, network correlations, random graph models, models of network growth
and preferential attachment, and dynamical processes taking place on networks.},
added-at = {2006-01-24T08:42:05.000+0100},
author = {Newman, M. E. J.},
biburl = {https://www.bibsonomy.org/bibtex/2d53568209eef08fb0a8734cf34c59a71/hotho},
citeulike-article-id = {155},
eprint = {cond-mat/0303516},
interhash = {7bedd01cb4c06af9f5200b0fb3faa571},
intrahash = {d53568209eef08fb0a8734cf34c59a71},
keywords = {algorithm clustering complex_systems folksonomy information kdubiq network retrieval scale_free_networks small socialnetwork summerschool theory web web_graph world},
month = {March},
priority = {5},
timestamp = {2008-01-25T20:47:05.000+0100},
title = {The structure and function of complex networks},
url = {http://arxiv.org/abs/cond-mat/0303516},
year = 2003
}