Multi-duplicated Characterization of Graph Structures using Information Gain Ratio for Graph Neural Networks

Various graph neural networks (GNNs) have been proposed to solve node classification tasks in machine learning for graph data. GNNs use the structural information of graph data by aggregating the features of neighboring nodes. However, they fail to directly characterize and leverage the structural i...

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Hauptverfasser:	Oishi, Yuga, kaneiwa, Ken
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Learning
Online-Zugang:	Volltext bestellen
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