In this paper, we consider the link prediction problem, where we are given a partial snapshot of a network at some time and the goal is to predict the additional links formed at a ...
Janardhan Rao Doppa, Jun Yu, Prasad Tadepalli, Lis...
In this paper3 , we use Bayesian Networks as a means for unsupervised learning and anomaly (event) detection in gas monitoring sensor networks for underground coal mines. We show t...
X. Rosalind Wang, Joseph T. Lizier, Oliver Obst, M...
Although a large body of work are devoted to finding communities in static social networks, only a few studies examined the dynamics of communities in evolving social networks. I...
— We introduce a graph-based relational learning approach using graph-rewriting rules for temporal and structural analysis of biological networks changing over time. The analysis...
An increasing number of social networking platforms are giving users the option to endorse entities that they find appealing, such as videos, photos, or even other users. We defin...