Decoupling graph convolutional networks for large-scale supervised classification
Mariia Koreneva, Alexander A. Visheratin, Denis A. Nasonov · Procedia Computer Science · 2020
We present a new approach to large-scale supervised heterogeneous graph classification. We decouple a large heterogeneous graph into smaller homogeneous ones. In this paper, we show that our model provides results close to the state-of-the-art model while greatly simplifying calculations and makes it possible to process complex heterogeneous graphs on a much larger scale.