Unknown

Dataset Information

Toward link predictability of complex networks.


ABSTRACT: The organization of real networks usually embodies both regularities and irregularities, and, in principle, the former can be modeled. The extent to which the formation of a network can be explained coincides with our ability to predict missing links. To understand network organization, we should be able to estimate link predictability. We assume that the regularity of a network is reflected in the consistency of structural features before and after a random removal of a small set of links. Based on the perturbation of the adjacency matrix, we propose a universal structural consistency index that is free of prior knowledge of network organization. Extensive experiments on disparate real-world networks demonstrate that (i) structural consistency is a good estimation of link predictability a

SUBMITTER: Lu L 

PROVIDER: S-EPMC4345601 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature