Second, different from conventional KG representation learning, entity alignment requires one-to-one mapping, which implies that the similar entities sharing common neighbors cannot be embeded closely, otherwise they shall be aligned incorrectly as shown in Figure 1.
as for cross-graph model, we propose to utilize an extended Graph Attention Network (GAT) (Vaswani et al., 2017) as our crossgraph model that allows robustly encoding of KGs.