論文閱讀 《Progressive Self-Supervised Attention Learning for Aspect-Level Sentiment Analysis》
這篇文章也是針對aspect-level SA的一篇文章，其實準確的說更像一篇針對注意力機制的文章，提出了SA模型目前注意力機制的缺陷：過度注意高頻詞，忽略了低頻次，本文用了兩個技巧：第一個是迭代的mask注意力權重最大的詞，第二個是加入了一個正則化項
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相關文章
- 1. Progressive Self-Supervised Attention Learning forAspect-Level Sentiment Analysis論文閱讀
- 2. 《Progressive Self-Supervised Attention Learning for Aspect-Level Sentiment Analysis》學習筆記
- 3. 論文閱讀筆記：Transfer Learning for Deep Sentiment Analysis
- 4. 【l論文閱讀】An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment Analysis
- 5. VistaNet: Visual Aspect Attention Network for Multimodal Sentiment Analysis 論文解讀
- 6. 《Review Sentiment Analysis Based on Deep Learning》論文閱讀筆記
- 7. 論文閱讀 《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閱讀筆記
- 9. 論文閱讀：Leveraging multimodal information for event summarization and concept-level sentiment analysis
- 10. SentiLR:Linguistic Knowledge Enhanced Language Representation for Sentiment Analysis 論文閱讀筆記