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弱监督词向量 (Weakly Supervised Word2Vec)

弱监督词向量使用自动生成、带噪声或启发式生成的标签来训练 Word2Vec 风格的词嵌入，而不是昂贵的人工标注。通过利用标注函数、远程监督或基于关键词的规则来分配软标签，该方法即使在缺乏大规模手动标注语料库的情况下，也能实现领域自适应的词语表示。

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弱监督词向量 (Weakly Supervised Word2Vec)
[需翻译标题：BERT-based Classi…Doc2Vec半监督Word2Vec句子嵌入弱监督句子嵌入Word2Vec

来源

  1. Mikolov, T., Sutskever, I., Chen, K., Corrado, G., & Dean, J. (2013). Distributed representations of words and phrases and their compositionality. Advances in Neural Information Processing Systems, 26. link ↗
  2. Ratner, A. J., De Sa, C. M., Wu, S., Selsam, D., & Re, C. (2016). Data programming: Creating large training sets, quickly. Advances in Neural Information Processing Systems, 29. link ↗

如何引用本页

ScholarGate. (2026, June 3). Weakly Supervised Word2Vec (Word Embeddings with Weak Supervision). ScholarGate. https://scholargate.app/zh/deep-learning/weakly-supervised-word2vec

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ScholarGate — Weakly supervised Word2Vec (Weakly Supervised Word2Vec (Word Embeddings with Weak Supervision)). 于 2026-06-15 检索自 https://scholargate.app/zh/deep-learning/weakly-supervised-word2vec · 数据集： https://doi.org/10.5281/zenodo.20539026