Before revision:  In the proposed framework, the traditional graph convolution operation is generalized into two parts: feature transformation and feature aggregation, which gives  CTGCN more flexibility and enables  CTGCN to learn connective and structural information under the same framework.
After revision:  In the proposed framework, the traditional graph convolution operation is generalized into two phases, feature transformation and feature aggregation, which gives CTGCN more flexibility and enables CTGCN to learn connective and structural information under the same framework.