Review of graph neural network in text classification
M Malekzadeh, P Hajibabaee, M Heidari… - 2021 IEEE 12th …, 2021 - ieeexplore.ieee.org
Text classification is one of the fundamental problems in Natural Language Processing
(NLP). Several research studies have used deep learning approaches such as Convolution …
(NLP). Several research studies have used deep learning approaches such as Convolution …
Graph neural networks for text classification: A survey
Text Classification is the most essential and fundamental problem in Natural Language
Processing. While numerous recent text classification models applied the sequential deep …
Processing. While numerous recent text classification models applied the sequential deep …
Graph convolutional networks for text classification
Text classification is an important and classical problem in natural language processing.
There have been a number of studies that applied convolutional neural networks …
There have been a number of studies that applied convolutional neural networks …
Text level graph neural network for text classification
Recently, researches have explored the graph neural network (GNN) techniques on text
classification, since GNN does well in handling complex structures and preserving global …
classification, since GNN does well in handling complex structures and preserving global …
Deep attention diffusion graph neural networks for text classification
Text classification is a fundamental task with broad applications in natural language
processing. Recently, graph neural networks (GNNs) have attracted much attention due to …
processing. Recently, graph neural networks (GNNs) have attracted much attention due to …
Deep learning, graph-based text representation and classification: a survey, perspectives and challenges
Recently, with the rapid developments of the Internet and social networks, there have been
tremendous increase in the amount of complex-structured text resources. These information …
tremendous increase in the amount of complex-structured text resources. These information …
Text FCG: Fusing contextual information via graph learning for text classification
Y Wang, C Wang, J Zhan, W Ma, Y Jiang - Expert Systems with Applications, 2023 - Elsevier
Text classification as a fundamental task in Natural Language Processing (NLP). Graph
neural networks can better handle the large amount of information in text, and effective and …
neural networks can better handle the large amount of information in text, and effective and …
Hetegcn: heterogeneous graph convolutional networks for text classification
We consider the problem of learning efficient and inductive graph convolutional networks for
text classification with a large number of examples and features. Existing state-of-the-art …
text classification with a large number of examples and features. Existing state-of-the-art …
Graph fusion network for text classification
Text classification is an important and classical problem in natural language processing.
Recently, Graph Neural Networks (GNNs) have been widely applied in text classification …
Recently, Graph Neural Networks (GNNs) have been widely applied in text classification …
Induct-gcn: Inductive graph convolutional networks for text classification
Text classification aims to assign labels to textual units by making use of global information.
Recent studies have applied graph neural network (GNN) to capture the global word co …
Recent studies have applied graph neural network (GNN) to capture the global word co …