计算机科学 ›› 2022, Vol. 49 ›› Issue (2): 279-284.doi: 10.11896/jsjkx.201200062
所属专题： 自然语言处理 虚拟专题
张虎, 柏萍
ZHANG Hu, BAI Ping
摘要： 随着图神经网络技术在自然语言处理领域中的广泛应用,基于图神经网络的文本分类研究受到了越来越多的关注,文本构图是图神经网络应用到文本分类中的一项重要研究任务,已有方法在构图时通常不能有效捕获句子中远距离词语的依赖关系。短文本分类是待分类文本中普遍较短的一类特殊文本分类任务,传统的文本表示通常比较稀疏且缺乏丰富的语义信息。基于此,文中提出了一种融入远距离词语依赖关系进行构图的图卷积短文本分类方法。首先结合词语共现关系、文档和词语之间的包含关系、远距离词语依赖关系为整个文本语料库构建一个文本图;然后将文本图输入到图卷积神经网络,通过2层卷积后,对每个文档节点进行类别预测。在on_line_shopping_10_cats、中文论文摘要和酒店评论3个数据集上的实验结果表明,所提方法相比已有基线模型取得了更好的效果。
中图分类号:
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