Then, we propose a graph matching model to estimate the probability that G 1 and G 2 are describing the same entity.
the matching model includes the following four layers: Input Representation Layer The goal of this layer is to learn embeddings for entities that occurred in topic entity graphs by using a GCN (henceforth GCN 1 ) (Xu et al., 2018a).