Bidirectional-GRU based on attention mechanism for aspect-level Sentiment Analysis

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	Bidirectional-GRU based on attention mechanism for aspect-level Sentiment Analysis
	Zhang DY(张丁一)2,3 ; Zhai PH(翟鹏华)1,2,3
	2019
会议日期	February 22-24, 2019
会议地点	Zhuhai, China
关键词	sentimental analysis deep learning machine learning attention mechanism aspect-level
页码	86-90
英文摘要	Aspect-level sentiment analysis is a fine-grained natural language processing task. For traditional deep learning models, they cannot accurately construct the aspect-level sentiment features. Such as, for the sentence of “the movie is very funny, but the seats in the theater is uncomfortable.” For the movie, the polarity is positive, but it is negative for seats. To deal with this problem, we propose a bidirectional gated recurrent units neural network model that integrates the attention mechanism to solve the task of aspect-level sentiment analysis. The attention mechanism can focus on the different parts of a sentence when the sentence has several different aspects. Because we use a bidirectional gated recurrent unit, we can get independent context semantic information and get the deeper aspect sentiment information from the front and back, so that we can deal with the specific aspect sentiment polarity. Finally, we experiment on SemEval-2014 dataset and twitter dataset, the result of experiments verified the effectiveness of attention-based bidirectional gated recurrent unit on the aspect sentiment analysis. The model achieves good performance at different datasets and has further improvement comparing to previous models.
源文献作者	Asia Society of Researchers ; Metropolitan State University of Denver ; Southwest Jiaotong University ; University of Macau
产权排序	1
会议录	ACM International Conference Proceeding Series
会议录出版者	ACM
会议录出版地	New York
语种	英语
ISBN号	978-1-4503-6600-7
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/24685]
专题	沈阳自动化研究所_数字工厂研究室
通讯作者	Zhai PH(翟鹏华)
作者单位	1.University of Chinese Academy of Science, Beijing 100049, China 2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China 3.Shenyang Institute of Automation, Chinese Academy of Science, Shenyang 110016, China
推荐引用方式 GB/T 7714	Zhang DY,Zhai PH. Bidirectional-GRU based on attention mechanism for aspect-level Sentiment Analysis[C]. 见:. Zhuhai, China. February 22-24, 2019.