1.College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350116 2.Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing,Fuzhou University, Fuzhou 350116 3.College of Electronics and Information Science, Fujian Jiang-xia University, Fuzhou 350108 4.Key Laboratory of Network Data Science and Technology, Chinese Academy of Sciences, Beijing 100190
Abstract In the current memory network model, the words of the context are independent of each other, and the influence of word order information on microblog sentiment is not taken into account. Therefore, a perspective level microblog sentiment classification method based on convolutional memory network is proposed. In the method, memory network can effectively model the semantic relation between the query and the text. Consequently, the view and the text are abstracted via this property. Furthermore, the word order in context is extended by convolutional operation. Then, the result is utilized to capture the attention signals of different terms in context for the weighted representation of text. Experimental results on three public datasets indicate that the proposed method achieves higher accuracies and Macro-F1 values compared with other methods.
Fund:Supported by National Natural Science Foundation of China(No.U1605251), Open Project of Key Laboratory of Network Data Science & Technology of Chinese Academy of Sciences(No.CASNDST201606), Director′s Project Fund of Key Laboratory of Trustworthy Distributed Computing and Service of Ministry of Education(No.2017KF01), Natural Science Foundation of Fujian Province(No.2017J01755), CERNET Innovation Project(No.NGII20150901)
Corresponding Authors:
GUI Lin, born in 1987, Ph.D., lecturer. His research inte-rests include sentiment analysis and machine learning.
About author:: LIAO Xiangwen, born in 1980, Ph.D., associate professor. His research interests include opinion mining and sentiment analysis.XIE Yuanyuan, born in 1993, master student. Her research interests include opi-nion mining and sentiment analysis.WEI Jingjing, born in 1984, Ph.D., lecturer. Her research interests include opinion mining.CHENG Xueqi, born in 1971,Ph.D., professor. His research interests include big data analysis and mining.CHEN Guolong, born in 1965, Ph.D., professor. His research interests include inte-lligent information processing.
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2018, Vol. 31 
