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半监督情感分析

半监督情感分析结合了少量手动标记的文本样本和大量未标记的文本池来训练意见分类器。通过自训练、标签传播或一致性正则化等方法将情感信号从标记种子传播到未标记数据，该方法在无需标注大型语料库的成本下即可实现具有竞争力的准确性。

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半监督情感分析
[需翻译标题：BERT-based Classi…LDA主题模型自监督情感分析半监督式BERT分类

来源

  1. Zhu, X. (2005). Semi-Supervised Learning Literature Survey. Technical Report 1530, Computer Sciences, University of Wisconsin-Madison. link ↗
  2. Pang, B., & Lee, L. (2008). Opinion Mining and Sentiment Analysis. Foundations and Trends in Information Retrieval, 2(1–2), 1–135. DOI: 10.1561/1500000011 ↗

如何引用本页

ScholarGate. (2026, June 3). Semi-supervised Sentiment Analysis (Label Propagation and Self-Training for Opinion Mining). ScholarGate. https://scholargate.app/zh/deep-learning/semi-supervised-sentiment-analysis

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ScholarGate — Semi-supervised Sentiment Analysis (Semi-supervised Sentiment Analysis (Label Propagation and Self-Training for Opinion Mining)). 于 2026-06-15 检索自 https://scholargate.app/zh/deep-learning/semi-supervised-sentiment-analysis · 数据集： https://doi.org/10.5281/zenodo.20539026