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Open AccessArticle
Enhanced Text Classification with Label-Aware Graph Convolutional Networks
by
Ming-Yen Lin
Ming-Yen Lin 1
,
Hsuan-Chun Liu
Hsuan-Chun Liu 1 and
Sue-Chen Hsush
Sue-Chen Hsush 2,*
1
Department of Information Engineering and Computer Science, Feng Chia University, Taichung 407, Taiwan
2
Department of Information Management, Chaoyang University of Technology, Taichung 413, Taiwan
*
Author to whom correspondence should be addressed.
Electronics 2024, 13(15), 2944; https://doi.org/10.3390/electronics13152944 (registering DOI)
Submission received: 30 June 2024
/
Revised: 18 July 2024
/
Accepted: 25 July 2024
/
Published: 25 July 2024
Abstract
Text classification is an important research field in text mining and natural language processing, gaining momentum with the growth of social networks. Despite the accuracy advancements made by deep learning models, existing graph neural network-based methods often overlook the implicit class information within texts. To address this gap, we propose a graph neural network model named LaGCN to improve classification accuracy. LaGCN utilizes the latent class information in texts, treating it as explicit class labels. It refines the graph convolution process by adding label-aware nodes to capture document–word, word–word, and word–class correlations for text classification. Comparing LaGCN with leading-edge models like HDGCN and BERT, our experiments on Ohsumed, Movie Review, 20 Newsgroups, and R8 datasets demonstrate its superiority. LaGCN outperformed existing methods, showing average accuracy improvements of 19.47%, 10%, 4.67%, and 0.4%, respectively. This advancement underscores the importance of integrating class information into graph neural networks, setting a new benchmark for text classification tasks.
Share and Cite
MDPI and ACS Style
Lin, M.-Y.; Liu, H.-C.; Hsush, S.-C.
Enhanced Text Classification with Label-Aware Graph Convolutional Networks. Electronics 2024, 13, 2944.
https://doi.org/10.3390/electronics13152944
AMA Style
Lin M-Y, Liu H-C, Hsush S-C.
Enhanced Text Classification with Label-Aware Graph Convolutional Networks. Electronics. 2024; 13(15):2944.
https://doi.org/10.3390/electronics13152944
Chicago/Turabian Style
Lin, Ming-Yen, Hsuan-Chun Liu, and Sue-Chen Hsush.
2024. "Enhanced Text Classification with Label-Aware Graph Convolutional Networks" Electronics 13, no. 15: 2944.
https://doi.org/10.3390/electronics13152944
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