In practice, complex systems often change over time, and the temporal characteristics of a complex network make their behavior difficult to predict. Traditional link prediction methods based on structural similarity are good for mining underlying information from static networks, but do not...

Link prediction in directed network is attracting growing interest among many network scientists. Compared with predicting the existence of a link, determining its direction is more complicated. In this paper, we propose an efficient solution named Local Directed Path to predict link direction....

Plenty of algorithms for link prediction have been proposed to extract missing information, identify spurious interactions, reconstruct networks, and so on. Stochastic block models are one of the most accurate methods among all of them. However, this algorithm is designed only for simple graphs...