Before revision:  A novel graph embedding method is proposed to generate state representations for nodes and extracted subgraphs jointly at each step . Experiments on real graph datasets demonstrate that our model performs favorably to exact MCS solvers and supervised neural graph matching network models in terms of accuracy and efficiency .
After revision:  A novel graph embedding method is proposed to generate state representations for nodes and extracted subgraphs jointly at each step . Experiments on synthetic and real-world large graph pairs demonstrate that our model performs favorably to exact MCS solvers and supervised neural graph matching network models in terms of accuracy and efficiency .