A Multi-emotion Classification Method Based on BLSTM-MC in Code-Switching Text

摘要：

　　Most of the previous emotion classifications are based on binary or ternary classifications,and the final emotion classification results contain only one type of emotion.There is little research on multi-emotional coexistence,which has certain limitations on the restoration of humans true emotions.Aiming at these deficiencies,this paper proposes a Bidirectional Long-Short Term Memory Multiple Classifiers(BLSTM-MC)model to study the five classification problems in code-switching text,and obtains text contextual relations through BLSTM-MC model.It fully considers the relationship between different emotions in a single post,at the same time,the Attention mechanism is introduced to find the importance of different features and predict all emotions expressed by each post.The model achieved third place in all submissions in the conference NLP&&CC_task1 2018.

关键词： Multiple emotion classification Code-switching texts Attention mechanism BLSTM multiple classifiers

作者: Tingwei Wang Xiaohua Yang Chunping Ouyang Aodong Guo Yongbin Liu Zhixing Li

作者单位: School of Computer,University of South China,Hengyang 421001,China College of Information Engineering,Xinhua University,Hefei 230031,China Chongqing University of Posts and Telecommunications,Chongqing 400065,China

会议类型: 国际会议

会议名称: 2018自然语言处理与中文计算国际会议(NLPCC2018)

会议地点: 呼和浩特

会议语种:英文

页码: 190-199

在线出版日期: 2018-08-26（万方平台首次上网日期，不代表论文的发表时间）