NAGphormer+: A Tokenized Graph Transformer With Neighborhood Augmentation for Node Classification in Large Graphs

Graph Transformers, emerging as a new architecture for graph representation learning, suffer from the quadratic complexity and can only handle graphs with at most thousands of nodes. To this end, we propose a Neighborhood Aggregation Graph Transformer (NAGphormer) that treats each node as a sequence...

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Veröffentlicht in:	IEEE transactions on big data 2024-12, p.1-14
Hauptverfasser:	Chen, Jinsong, Liu, Chang, Gao, Kaiyuan, Li, Gaichao, He, Kun
Format:	Artikel
Sprache:	eng
Schlagworte:	Aggregates Benchmark testing Big Data Data augmentation Data models Encoding Graph neural networks graph transformers large graphs neighborhood token Training Transformers Vectors
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