Graph Convolutional Network Design for Node Classification Accuracy Improvement

Graph Convolutional Network Design for Node Classification Accuracy Improvement

Graph convolutional networks (GCNs) provide an advantage in node classification tasks for graph-related data structures. In this paper, we propose a GCN model for enhancing the performance of node classification tasks. We design a GCN layer by updating the aggregation function using an updated value...

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Bibliographic Details
Main Authors: Mohammad Abrar Shakil Sejan, Md Habibur Rahman, Md Abdul Aziz, Jung-In Baik, Young-Hwan You, Hyoung-Kyu Song
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Mathematics
Subjects:
graph data structure
graph learning
graph convolutional network
node classification
Online Access:https://www.mdpi.com/2227-7390/11/17/3680

Internet

https://www.mdpi.com/2227-7390/11/17/3680

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