Hypergraph Neural Networks Based on Enclosing Subgraph Extraction for Temporal Link Prediction

The Graph Neural Network (GNN) methods based on enclosing subgraph extraction have achieved excellent results in static graph link prediction tasks. However, most real-world networks are dynamic and evolve over time; the traditional models cannot capture temporal evolution. Moreover, the existing te...

詳細記述

書誌詳細

主要な著者:	Ying Zhao, Xiangxu Meng, Liang Chen, Junjun Chen, Atul Sajjanhar
フォーマット:	Artigo
言語:	Inglês
出版事項:	IEEE 2025-01-01
シリーズ:	IEEE Access
主題:	Collapsed graph hypergraph hypergraph neural network link prediction self-attention mechanism
オンライン･アクセス:	https://ieeexplore.ieee.org/document/11168471/
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