计算机工程与应用2024，Vol.60Issue(19)：1-17,17.DOI:10.3778/j.issn.1002-8331.2403-0142
基于图神经网络的文本分类方法研究综述
Review of Text Classification Methods Based on Graph Neural Networks
摘要
Abstract
Text classification is an important task in the field of natural language processing,aiming to assign given text data to a predefined set of categories.Traditional text classification methods can only handle data in Euclidean space and cannot process non-Euclidean data such as graphs.For text data with graph structure,it is not directly processable and can-not capture the non-Euclidean structure in the graph.Therefore,how to apply graph neural networks to text classification tasks is one of the current research hotspots.This paper reviews the text classification methods based on graph neural net-works.Firstly,it outlines the traditional text classification methods based on machine learning and deep learning,and sum-marizes the background and principles of graph convolutional neural networks.Secondly,it elaborates on the text classifi-cation methods based on graph neural networks according to different types of graph networks,and conducts an in-depth analysis of the application of graph neural network models in text classification.Then,it compares the current text classifi-cation models based on graph neural networks through comparative experiments and discusses the classification perfor-mance of the models.Finally,it proposes future research directions to further promote the development of this field.关键词
文本分类/自然语言处理/图神经网络/图网络Key words
text classification/natural language processing/graph neural networks/graph networks分类
信息技术与安全科学引用本文复制引用
苏易礌,李卫军,刘雪洋,丁建平,刘世侠,李浩南,李贯峰..基于图神经网络的文本分类方法研究综述[J].计算机工程与应用,2024,60(19):1-17,17.基金项目
国家自然科学基金(62066038,61962001) （62066038,61962001）
宁夏自然科学基金(2021AAC03215) （2021AAC03215）
中央高校科研业务费(2021JCYJ12). （2021JCYJ12）
