Finding of the missed values in the adjacency matrix of a big undirected weighted graph by utilizing probabilistic graphical models. The adjacency matrix's values were modeled with Poisson distribution and Gamma prior. Three approaches were investigated for solving the problem including EM algorithm, Variational Inference, and Gibbs sampling method.