论文阅读 《Progressive Self-Supervised Attention Learning for Aspect-Level Sentiment Analysis》
这篇文章也是针对aspect-level SA的一篇文章，其实准确的说更像一篇针对注意力机制的文章，提出了SA模型目前注意力机制的缺陷：过度注意高频词，忽略了低频次，本文用了两个技巧：第一个是迭代的mask注意力权重最大的词，第二个是加入了一个正则化项
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相关文章
- 1. Progressive Self-Supervised Attention Learning forAspect-Level Sentiment Analysis论文阅读
- 2. 《Progressive Self-Supervised Attention Learning for Aspect-Level Sentiment Analysis》学习笔记
- 3. 论文阅读笔记：Transfer Learning for Deep Sentiment Analysis
- 4. 【l论文阅读】An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment Analysis
- 5. VistaNet: Visual Aspect Attention Network for Multimodal Sentiment Analysis 论文解读
- 6. 《Review Sentiment Analysis Based on Deep Learning》论文阅读笔记
- 7. 论文阅读 《An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment Analysis》
- 8. 2017emnlp---Recurrent Attention Network on Memory for Aspect Sentiment Analysis阅读笔记
- 9. 论文阅读：Leveraging multimodal information for event summarization and concept-level sentiment analysis
- 10. SentiLR:Linguistic Knowledge Enhanced Language Representation for Sentiment Analysis 论文阅读笔记