Machine learningDeep learning / NLP / CV
领域自适应情感分析
领域自适应情感分析在标记的一个或多个源域（例如，产品评论）上训练情感模型，并将其适配到标签稀缺或缺失的目标域（例如，社交媒体帖子或新闻）。通过弥合域之间的词汇和分布差异，它可以在每个目标域不需要大量标记语料库的情况下实现强大的情感分类。
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来源
- Blitzer, J., Dredze, M., & Pereira, F. (2007). Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classification. Proceedings of the 45th Annual Meeting of the Association for Computational Linguistics (ACL), 440–447. link ↗
- Pan, S. J., Ni, X., Sun, J.-T., Yang, Q., & Chen, Z. (2010). Cross-domain sentiment classification via spectral feature alignment. Proceedings of the 19th International Conference on World Wide Web (WWW), 751–760. DOI: 10.1145/1772690.1772767 ↗
如何引用本页
ScholarGate. (2026, June 3). Domain-adaptive Sentiment Analysis (Cross-Domain Opinion Mining with Domain Adaptation). ScholarGate. https://scholargate.app/zh/deep-learning/domain-adaptive-sentiment-analysis
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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