Although DeepWalk is effective on learning embeddings of the topological structure, when dealing with a network classification task, it lacks a mechanism to optimize the objective of the target task and thus often leads to suboptimal embeddings.
for our focus of relational network classification, we would like the embeddings to be both representing the topological structure of the network actors and discriminative in predicting the class labels of actors.