 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.
<coherence>  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.
 Different from existing studies, we propose to consider both spatial connection and human mobility . With a flow graph and a spatial graph through a GCN-aided skip-gram model named GCN-L2V.