SAAN: A Sentiment-Aware Attention Network for Sentiment Analysis
文献类型：会议论文
| 作者 | Zeyang Lei; Yujiu Yang; Min Yang |
| 出版日期 | 2018 |
| 会议日期 | 2018 |
| 会议地点 | 美国芝加哥 |
| 英文摘要 | Analyzing public opinions towards products, services and social events is an important but challenging task. Despite the remarkable successes of deep neural networks in sentiment analysis, these approaches do not make full use of the prior sentiment knowledge (e.g., sentiment lexicon, negation words, intensity words). In this paper, we propose a Sentiment- Aware Attention Network (SAAN) to boost the performance of sentiment analysis, which adopts a three-step strategy to learn the sentiment-specific sentence representation. First, we design a word-level mutual attention mechanism to model word-level correlation. Next, a phrase-level convolutional attention is designed to obtain phrase-level correlation. Finally, a sentence-level multi-source attention mechanism is adopted to capture various sentimental information from multiple dimensions. The experiments on Movie Review (MR) and Stanford Sentiment Treebank (SST) show that our model consistently outperform the previous methods for sentiment analysis. |
| 语种 | 英语 |
| URL标识 | 查看原文 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/14092]  |
| 专题 | 深圳先进技术研究院_数字所 |
| 推荐引用方式 GB/T 7714 | Zeyang Lei,Yujiu Yang,Min Yang. SAAN: A Sentiment-Aware Attention Network for Sentiment Analysis[C]. 见:. 美国芝加哥. 2018. |
入库方式： OAI收割
来源：深圳先进技术研究院
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