Targeted Aspect-Based Sentiment Analysis via Embedding Commonsense Knowledge into an Attentive LSTM
Targeted Aspect-Based Sentiment Analysis via Embedding Commonsense Knowledge into an Attentive LSTM (AAAI-18) 原文下载 研究方向 情感分析 研究目的 分析人们对于特定属性的情感倾向是自然语言理解中的一项重要任务。在本文中，提出了一种对于实体属性情感分析的新颖的方法，通过加入常识知识来进行属
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相关文章
- 1. 《Attentional Encoder Network for Targeted Sentiment Classification》
- 2. 《Knowledge-enriched Two-layered Attention Network for Sentiment Analysis》
- 3. 【EMNLP2019】Event Representation Learning Enhanced with External Commonsense Knowledge
- 4. Predicting Human Eye Fixations via an LSTM-based Saliency Attentive Model
- 5. LSTM Networks for Sentiment
- 6. [论文] Aspect Based Sentiment Analysis with Gated Convolutional Networks
- 7. SentiLR:Linguistic Knowledge Enhanced Language Representation for Sentiment Analysis 论文阅读笔记
- 8. Sentiment Analysis resources
- 9. 《Aspect-Level Sentiment Analysis Via Convolution over Dependency Tree》阅读笔记
- 10. (ACL2019)Open-DomainTargeted Sentiment Analysis via Span-Based Extraction and Classification