Transportation networks play a crucial role in society by enabling the smooth movement of
people and goods during regular times and acting as arteries for evacuations during …

Graph Neural Networks (GNNs) have witnessed great advancement in the field of neural
networks for processing graph datasets. Graph Convolutional Networks (GCNs) have …

Background Widespread bioinformatics applications such as drug repositioning or drug–
drug interaction prediction rely on the recent advances in machine learning, complex …

Social networks are widely considered as the most important tool to connect people. The last
century saw a massive increase in the number of links between users. Many nodes and/or …

Most of the best performing link prediction ranking measures evaluate the common
neighbourhood of a pair of nodes in a network, in order to assess the likelihood of a new …

Human trafficking refers to the transportation, harboring, or obtaining of persons through
force, fraud, and coercion for the purpose of exploitation. Every year, millions of individuals …

We propose and evaluate two complementary heuristics to speed up exact computation of
the shortest-path betweenness centrality (BC). Both heuristics are relatively simple …

Software Defined Networking (SDN) decouples the control and data planes and moves the
control logic to the SDN controllers. The traffic in the control plane is either related to the …

In this paper we introduce a novel model for link prediction in social network based on a
quantitative growth and diffusion model of node features which are used to compute …

For link prediction, Common Neighbours (CN) ranking measures allow to discover quality
links between nodes in a social network, assessing the likelihood of a new link based on the …