 This model embeds context information in human mobility and spatial information. By doing so, GCN-L2V is able to capture relationships among locations and provide a better notion of semantic similarity in a spatial environment.
<clarity>  This model embeds context information in human mobility and spatial information. By doing so, GCN-L2V is able to capture relationships among locations and provide a better notion of semantic similarity in a spatial environment.
 This model embeds context information into vector representations. GCN-L2V is able to capture relationships among locations and provide a better notion of semantic similarity in a spatial environment.