ATPGNN: Reconstruction of Neighborhood in Graph Neural Networks With Attention-Based Topological Patterns
Graph Neural Networks (GNNs) have been applied in many fields of semi-supervised node classification for non-Euclidean data. However, some GNNs cannot make good use of positive information brought by nodes which are far away from each central node for aggregation operations. These remote nodes with...
Main Authors: | Kehao Wang, Hantao Qian, Xuming Zeng, Mozi Chen, Kezhong Liu, Kai Zheng, Pan Zhou, Dapeng Wu |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2021-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9319003/ |
Similar Items
-
Bert-based graph unlinked embedding for sentiment analysis
by: Youkai Jin, et al.
Published: (2023-12-01) -
Multi-Duplicated Characterization of Graph Structures Using Information Gain Ratio for Graph Neural Networks
by: Yuga Oishi, et al.
Published: (2023-01-01) -
Hierarchical Model Selection for Graph Neural Networks
by: Yuga Oishi, et al.
Published: (2023-01-01) -
Limits of Depth: Over-Smoothing and Over-Squashing in GNNs
by: Aafaq Mohi ud din, et al.
Published: (2024-03-01) -
Link Prediction for Node Featureless Networks Based on Faster Attention Mechanism
by: LI Yong, WU Jing-peng, ZHANG Zhong-ying, ZHANG Qiang
Published: (2022-04-01)