A Hierarchical multi-input and output Bi-GRU Model for Sentiment Analysis on Customer Reviews

摘要：

　　Multi-label sentiment classification on customer reviews is a practical challenging task in Natural Language Processing.In this paper,we propose a hierarchical multi-input and output model based bi-directional recurrent neural network,which both considers the semantic and lexical information of emotional expression.Our model applies two independent Bi-GRU layer to generate part of speech and sentence representation.Then the lexical information is considered via attention over output of softmax activation on part of speech representation.In addition,we combine probability of auxiliary labels as feature with hidden layer to capturing crucial correlation between output labels.The experimental result shows that our model is computationally efficient and achieves breakthrough improvements on customer reviews dataset.

作者: Liujie Zhang Yanquan Zhou Xiuyu Duan Ruiqi Chen

作者单位: School of Computer Science,Beijing University of Posts and Telecommunications,Beijing,China School of Computer Science,Beijing University of Posts and Telecommunications,Beijing,China;Engineer

会议类型: 国际会议

会议名称: The 1st International Symposium on Application of Materials Science and Energy Materials (SAMSE 2017)

会议地点: 上海

会议语种:英文

页码: 1-6

在线出版日期: 2017-12-28（万方平台首次上网日期，不代表论文的发表时间）