The main aim of this talk is to develop iterative methods for solving a set of sparse non-negative tensor equations arising from information sciences such as networks analysis. Based on the structure of non-negative tensors, we develop Jacobi and Gauss-Seidel methods for solving such non-negative tensor equations. The advantage of the proposed method is that the multiplication of tensors with vectors is required at each iteration. Thus we have only sparse tensor-vector operations, and the set of non-negative tensor equations can be solved very efficiently. Experimental results on information retrieval by query search and community discovery in networksare reported to demonstrate that the effectiveness and efficiency of the proposed methods.