Supervised Random Walks for Predicting Links in Social Networks: A Study - Vihashini, A; Prabavathi, GT (International Journal of Computer Sciences and Engineering, 2025)
Predicting is future relationships from a given snapshot of a network or to infer the interactions among existing members that are likely to occur in the near future is called as link prediction. One of the interesting areas of research in social network is prediction of links. There are various techniques for inferring missing links or additional links that are not directly visible but may occur in the future. Random walk is a popular approach which uses node and edge features to solve the problem of link prediction. Supervised random walks combine the network structure with the characteristics of nodes and edges and acts as a powerful tool for predicting the missing and future links. In this paper a study has been made on various algorithms that uses supervised random walk approach for predicting links in social networks.