PUMA publications for /tag/world%20web%20clustering%20complex_systemshttps://puma.uni-kassel.de/tag/world%20web%20clustering%20complex_systemsPUMA RSS feed for /tag/world%20web%20clustering%20complex_systems2024-03-28T18:32:54+01:00The structure and function of complex networkshttps://puma.uni-kassel.de/bibtex/2d53568209eef08fb0a8734cf34c59a71/hothohotho2006-01-24T08:42:05+01:00algorithm clustering complex_systems folksonomy information kdubiq network retrieval scale_free_networks small socialnetwork summerschool theory web web_graph world <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="M. E. J. Newman" itemprop="url" href="/author/M.%20E.%20J.%20Newman"><span itemprop="name">M. Newman</span></a></span>. </span>(<em><span>März 2003<meta content="März 2003" itemprop="datePublished"/></span></em>)Tue Jan 24 08:42:05 CET 2006MarchThe structure and function of complex networks2003algorithm clustering complex_systems folksonomy information kdubiq network retrieval scale_free_networks small socialnetwork summerschool theory web web_graph world 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.