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The Jellyfish model of the World Wide Web topology represents the web as a core of highly connected nodes (web pages) surrounded by layers of less connected nodes. The Bow Tie model, on the other hand, divides the web into distinct zones: a strongly connected core, an 'IN' group leading into the core, an 'OUT' group leading out, and ...
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Recent interest in scale-free networks started in 1999 with work by Albert-László Barabási and Réka Albert at the University of Notre Dame who mapped the topology of a portion of the World Wide Web, [5] finding that some nodes, which they called "hubs", had many more connections than others and that the network as a whole had a power-law ...
The hierarchical network model is part of the scale-free model family sharing their main property of having proportionally more hubs among the nodes than by random generation; however, it significantly differs from the other similar models (Barabási–Albert, Watts–Strogatz) in the distribution of the nodes' clustering coefficients: as other models would predict a constant clustering ...
The degree distribution of the webgraph strongly differs from the degree distribution of the classical random graph model, the Erdős–Rényi model: [1] in the Erdős–Rényi model, there are very few large degree nodes, relative to the webgraph's degree distribution.
Giant Global Graph (GGG) is a name coined in 2007 by Tim Berners-Lee to help distinguish between the nature and significance of the content on the existing World Wide Web and that of a promulgated next-generation web, presumptively named Web 3.0. [1] In common usage, "World Wide Web" refers primarily to a web of discrete information objects ...
Network science is an academic field which studies complex networks such as telecommunication networks, computer networks, biological networks, cognitive and semantic networks, and social networks, considering distinct elements or actors represented by nodes (or vertices) and the connections between the elements or actors as links (or edges).
It is known that a wide variety of abstract graphs exhibit the small-world property, e.g., random graphs and scale-free networks. Further, real world networks such as the World Wide Web and the metabolic network also exhibit this property. In the scientific literature on networks, there is some ambiguity associated with the term "small world".