A Multi-sentiment-resource Enhanced Attention Network for Sentiment Classification
文献类型：会议论文
| 作者 | Yi Liu; Zeyang Lei; Yujiu Yang; Min Yang |
| 出版日期 | 2018 |
| 会议日期 | 2018 |
| 会议地点 | 澳大利亚墨尔本 |
| 英文摘要 | Deep learning approaches for sentiment classification do not fully exploit sentiment linguistic knowledge. In this paper, we propose a Multi-sentiment-resource Enhanced Attention Network (MEAN) to alleviate the problem by integrating three kinds of sentiment linguistic knowledge (e.g., sentiment lexicon, negation words, intensity words) into the deep neural network via attention mechanisms. By using various types of sentiment resources, MEAN utilizes sentiment-relevant information from different representation subspaces, which makes it more effective to capture the overall semantics of the sentiment, negation and intensity words for sentiment prediction. The experimental results demonstrate that MEAN has robust superiority over strong competitors. |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/14091]  |
| 专题 | 深圳先进技术研究院_数字所 |
| 推荐引用方式 GB/T 7714 | Yi Liu,Zeyang Lei,Yujiu Yang,et al. A Multi-sentiment-resource Enhanced Attention Network for Sentiment Classification[C]. 见:. 澳大利亚墨尔本. 2018. |
入库方式： OAI收割
来源：深圳先进技术研究院
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