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 …
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 …
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 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 …
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 …
Connecting the Dots: What Graph-Based Text Representations Work Best for Text Classification using Graph Neural Networks?
Given the success of Graph Neural Networks (GNNs) for structure-aware machine learning,
numerous studies have explored their application to text classification, as an alternative to …
numerous studies have explored their application to text classification, as an alternative to …
Graph convolutional networks for fast text classification
H Cai, S Lv, G Lu, T Li - 2022 4th International Conference on …, 2022 - ieeexplore.ieee.org
Recently, lots of studies have explored text classification methods based on graph
convolutional neural network (GCN) technology. Compared with traditional deep learning …
convolutional neural network (GCN) technology. Compared with traditional deep learning …
A semantic hierarchical graph neural network for text classification
S Hua, X Li, Y Jing, Q Liu - arXiv preprint arXiv:2209.07031, 2022 - arxiv.org
The key to the text classification task is language representation and important information
extraction, and there are many related studies. In recent years, the research on graph neural …
extraction, and there are many related studies. In recent years, the research on graph neural …
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 …
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 …