Before revision: This paperpresents a novel neural architecture search (NAS)framework for graph neural networks (GNNs) .
After revision: In this paper, we propose a novel framework to automatically utilize task-dependent semantic information which is encoded in heterogeneous information networks (HINs). Specifically, we search for a meta graph, which can capture more complex semantic relations than a meta path, to determine how graph neural networks (GNNs) .