Before revision:  Specifically, each of the input graphs is partitioned into a set of subgraphs to directly extract the local structural features firstly . Next, a learnable embedding function is used to map each subgraph into an embedding vector.
After revision:  Specifically, each of the input graphs is partitioned into a set of subgraphs to directly extract the local structural features firstly . Next, a novel graph neural network with an attention mechanism is designed to map each subgraph into an embedding vector.