A latent parameter node-centric model for spatial networks.

ABSTRACT: Spatial networks, in which nodes and edges are embedded in space, play a vital role in the study of complex systems. For example, many social networks attach geo-location information to each user, allowing the study of not only topological interactions between users, but spatial interactions as well. The defining property of spatial networks is that edge distances are associated with a cost, which may subtly influence the topology of the network. However, the cost function over distance is rarely known, thus developing a model of connections in spatial networks is a difficult task. In this paper, we introduce a novel model for capturing the interaction between spatial effects and network structure. Our approach represents a unique combination of ideas from latent variable statistical model

SUBMITTER: Larusso ND 

PROVIDER: S-EPMC3781076 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature