A Recommendation Method Based on Link Prediction in Drug-Disease Bipartite Network

Abstract

Link prediction is one of the most important research topics in social network analysis. It estimates of possible future connections between nodes in the network taking advantage of network's current state. The link prediction also provides useful information to make comments about the future. In this study, a method for link prediction in the disease-drug network is proposed. Sofar, the most of studies done is usually based on connection prediction in single mode networks. This method has been applied on a bipartite such as disease-drug network, as apart from single mode networks. The results obtained from experiments by unsupervised prediction demonstrate that the proposed method has a good percentage of success.