Link prediction based on local random walk

The problem of missing link prediction in complex networks has attracted much attention recently. Two difficulties in link prediction are the sparsity and huge size of the target networks. Therefore, to design an efficient and effective method is of both theoretical interest and practical significance. In this letter, we proposed a method based on local random walk, which can give competitively good or even better prediction than other random-walk–based methods while having a much lower computational complexity.