Evaluating link prediction by diffusion processes in dynamic networks.

ABSTRACT: Link prediction (LP) permits to infer missing or future connections in a network. The network organization defines how information spreads through the nodes. In turn, the spreading may induce changes in the connections and speed up the network evolution. Although many LP methods have been reported in the literature, as well some methodologies to evaluate them as a classification task or ranking problem, none have systematically investigated the effects on spreading and the structural network evolution. Here, we systematic analyze LP algorithms in a framework concerning: (1) different diffusion process - Epidemics, Information, and Rumor models; (2) which LP method most improve the spreading on the network by the addition of new links; (3) the structural properties of the LP-evolved network

SUBMITTER: Vega-Oliveros DA 

PROVIDER: S-EPMC6658485 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature