MGCN: Semi-supervised Classification in Multi-layer Graphs with Graph Convolutional Networks.
Abstract
Graph embedding is an important approach for graph analysis tasks such as node classification and link prediction. The goal of graph embedding is to find a low dimensional representation of graph nodes that preserves the graph information. Recent methods like Graph Convolutional Network (GCN) try to consider node attributes (if available) besides node relations and learn node embeddings for unsupervised and semi-supervised tasks on graphs. On...
Paper Details
Title
MGCN: Semi-supervised Classification in Multi-layer Graphs with Graph Convolutional Networks.
Published Date
Nov 21, 2018
Journal
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Notes
History