On Fundamentals of Link Prediction

Link prediction is one of the most productive branches in network science, aiming to estimate the likelihoods of unobserved links based on known network topology. This paper critically examines four fundamental issues in link prediction, say network selection, link sampling, model training and algorithm evaluation. It reviews the current research progresses and highlights some significant yet unresolved issues that urgently require scientific answers.