@misc{newman03-structure,
        title = {The structure and function of complex networks},
        author = {M. E. J. Newman},
        month = {March},
        year = 2003,
        url = {http://arxiv.org/abs/cond-mat/0303516},
        lastdatemodified = {2006-10-07},
	pdf = {newman03-structure.pdf},
	read = {notread},
	lastname = {Newman},
	own = {notown},
	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.},
	biburl = {http://www.bibsonomy.org/bibtex/2d53568209eef08fb0a8734cf34c59a71/dbenz_test},
	keywords = {folksonomy_socialnetwork information small_world diploma_thesis complex_systems eventually_useful web_graph scale_free_networks clustering}
}

@misc{newman03-structure,
        title = {The structure and function of complex networks},
        author = {M. E. J. Newman},
        month = {March},
        year = 2003,
        url = {http://arxiv.org/abs/cond-mat/0303516},
        lastdatemodified = {2006-10-07},
	pdf = {newman03-structure.pdf},
	read = {notread},
	lastname = {Newman},
	own = {notown},
	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.},
	biburl = {http://www.bibsonomy.org/bibtex/2d53568209eef08fb0a8734cf34c59a71/dbenz},
	keywords = {folksonomy_socialnetwork information small_world diploma_thesis complex_systems eventually_useful web_graph scale_free_networks clustering}
}