DynGraph-BERT: Combining BERT and GNN Using Dynamic Graphs for Inductive Semi-Supervised Text Classification

DynGraph-BERT: Combining BERT and GNN Using Dynamic Graphs for Inductive Semi-Supervised Text Classification

The combination of Bidirecional Encoder Representations from Transformers (BERT) and Graph Neural Networks (GNNs) has been extensively explored in the text classification literature, usually employing BERT as a feature extractor combined with heterogeneous static graphs. BERT transfers information v...

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Bibliographic Details
Main Authors: Eliton Luiz Scardin Perin, Mariana Caravanti de Souza, Jonathan de Andrade Silva, Edson Takashi Matsubara
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Informatics
Subjects:
graph neural networks
semi-supervised
text classification
BERT model
node classification
graph building
Online Access:https://www.mdpi.com/2227-9709/12/1/20
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