Scale-free multiple-partite models towards information networks

Multiple-partite networks exist in the real world, such as engineering constructions consisted of workers and machines. We build up random multiple-partite network models and show their topological properties by means of well-known methods appeared in the Barabási-Albert model. We find some new characters of the Barabási-Albert model and BA-type models, and show a connection between the degree distribution P(k) and the cumulative distribution P
_cum
(k), and discuss the velocities of the models for the goal of classifying network models.