Abstract. We investigate a stochastic model for complex networks, based on a spatial embedding of the nodes, called the Spatial Preferred Attachment (SPA) model. In the SPA model, nodes have spheres of influence of varying size, and new nodes may only link to a node if they fall within its influence region. The spatial embedding of the nodes models the background knowledge or identity of the node, which influences its link environment. In this paper, we focus on the (directed) diameter, small separators, and the (weak) giant component of the model.
The study of complex networks, and in particular of social networks, has mostly concentrated on rela...
We investigate the use of stochastic approximation as a method of identifying conditions necessary t...
AbstractPreferential Attachment (PA), which was originally proposed in the Barabasi-Albert (BA) Mode...
<p>We investigate a stochastic model for complex networks, based on a spatial embedding of the nodes...
Abstract. We present a new stochastic model for complex networks, based on a spatial embedding of th...
Abstract. We present a new stochastic model for complex net-works, based on a spatial embedding of t...
Abstract. We present a new stochastic model for complex net-works, based on a spatial embedding of t...
AbstractThe spatial preferred attachment (SPA) model is a model for networked information spaces suc...
Spatial networks, in which nodes and edges are embedded in space, play a vital role in the study of ...
In this communication we present results concerning a generalization of the preferential attachment ...
The Spatial Preferential Attachment model is a spatial random graph used to model social networks. N...
We review and discuss the structural consequences of embedding a random network within a metric spac...
Most of real networks show a structure that can be represented quite well by means of growth and pro...
In this paper we present a framework for the extension of the Barabási-Albert model to heterogeneous...
We generalize the scale-free network model of Barabási and Albert (Science, 286 (1999) 509) by propo...
The study of complex networks, and in particular of social networks, has mostly concentrated on rela...
We investigate the use of stochastic approximation as a method of identifying conditions necessary t...
AbstractPreferential Attachment (PA), which was originally proposed in the Barabasi-Albert (BA) Mode...
<p>We investigate a stochastic model for complex networks, based on a spatial embedding of the nodes...
Abstract. We present a new stochastic model for complex networks, based on a spatial embedding of th...
Abstract. We present a new stochastic model for complex net-works, based on a spatial embedding of t...
Abstract. We present a new stochastic model for complex net-works, based on a spatial embedding of t...
AbstractThe spatial preferred attachment (SPA) model is a model for networked information spaces suc...
Spatial networks, in which nodes and edges are embedded in space, play a vital role in the study of ...
In this communication we present results concerning a generalization of the preferential attachment ...
The Spatial Preferential Attachment model is a spatial random graph used to model social networks. N...
We review and discuss the structural consequences of embedding a random network within a metric spac...
Most of real networks show a structure that can be represented quite well by means of growth and pro...
In this paper we present a framework for the extension of the Barabási-Albert model to heterogeneous...
We generalize the scale-free network model of Barabási and Albert (Science, 286 (1999) 509) by propo...
The study of complex networks, and in particular of social networks, has mostly concentrated on rela...
We investigate the use of stochastic approximation as a method of identifying conditions necessary t...
AbstractPreferential Attachment (PA), which was originally proposed in the Barabasi-Albert (BA) Mode...