Page 328 - 《软件学报》2025年第7期

黄靖 等: 基于特征融合动态图网络的多标签文本分类算法 3249

中将进一步探索和优化动态图网络在文本分类中的应用, 提高动态图网络的自适应性, 优化模型在不平衡数据集
和带噪声标签数据中的表现, 构建适应性更强的多标签文本分类算法. 同时, 本文的研究也存在一定的局限性, 例
如当数据集当中标签的数量过多时 (例如 AmazonCat-3M 数据集包含数百万个标签), 每个样本可能只与其中的小
部分标签关联. 随着标签数量的增多, 计算复杂性也会增加, 这给模型的训练带来了巨大的困难.

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