linkprediktion
Link prediction is a fundamental task in network analysis that involves predicting the existence of links between nodes in a network. It is widely used in various domains such as social network analysis, bioinformatics, and recommendation systems. The goal is to identify potential connections that are likely to form in the future based on the existing structure of the network.
There are several approaches to link prediction, broadly categorized into similarity-based methods, probabilistic models, and machine
Probabilistic models, like the Stochastic Block Model and Exponential Random Graph Models, use statistical techniques to
Machine learning techniques, including supervised and unsupervised learning, have also been applied to link prediction. Supervised
Link prediction is a challenging task due to the dynamic and complex nature of networks. However, it