首页 / 深度学习 / 半监督Doc2Vec Machine learning Deep learning / NLP / CV
半监督Doc2Vec 半监督Doc2Vec 扩展了 Le 和 Mikolov (2014) 的 Paragraph Vector 框架，通过同时在标记和未标记语料库上训练密集文档嵌入，利用可用的类别标签作为辅助信号来引导表示学习任务相关结构，同时仍然利用完整的未标记集合进行泛化。
速览
Originator Le, Q. V. & Mikolov, T. (base Doc2Vec); semi-supervised extensions by various authors circa 2015–2019
Year 2014–2017
Type Semi-supervised representation learning
DataType Text (labeled + unlabeled documents)
Subfamily Deep learning / NLP / CV 本页目录
Method map The neighbourhood of related methods — select a node to explore.
来源 Le, Q. V., & Mikolov, T. (2014). Distributed Representations of Sentences and Documents. Proceedings of the 31st International Conference on Machine Learning (ICML 2014), PMLR 32(2), 1188–1196. link ↗ Word2vec. Wikipedia. link ↗ 如何引用本页 APA BibTeX RIS 复制
ScholarGate. (2026, June 3). Semi-supervised Paragraph Vector (Semi-supervised Doc2Vec). ScholarGate. https://scholargate.app/zh/deep-learning/semi-supervised-doc2vec
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Which method? Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
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ScholarGate — Semi-supervised Doc2Vec (Semi-supervised Paragraph Vector (Semi-supervised Doc2Vec)). 于 2026-06-15 检索自 https://scholargate.app/zh/deep-learning/semi-supervised-doc2vec · 数据集： https://doi.org/10.5281/zenodo.20539026