QQ客服 官方微博 反馈留言

	SAAN: A Sentiment-Aware Attention Network for Sentiment Analysis
	Zeyang Lei; Yujiu Yang; Min Yang
	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
内容类型	会议论文
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.

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。