Node matching between complex networks has practical significance in many areas. However, most of the traditional node matching algorithms which based on the local topological information may lose their efficiencies in many realistic networks, especially in the network with high topological symmetry. In order to overcome this shortage, recently, we proposed a new method to calculate the similarity between two nodes of different networks by utilizing both topological and link-weight information, based on which we designed a weighted iterative node matching algorithm. We test this new algorithm on pairwise artificial networks of high topological symmetry and a pair of real Chinese-English language networks. The results show that the weighted iterative node matching algorithm behaves better than the pure topology based iterative node matching algorithm on this kind of networks.