Before revision:  Different from existing studies, we propose to consider both spatial connection and human mobility , and jointly learn the representations from a flow graph and a spatial graph through a GCN-aided skip-gram model named GCN-L2V. This model embeds context information in human mobility and spatial information.
After revision:  Different from existing studies, we propose to consider both spatial connection and human mobility , and jointly learn the representations from a flow graph and a spatial graph , it embeds context information in human mobility and spatial information.