End-to-End Neural Text Classification for Tibetan

摘要：

　　As a minority language,Tibetan has received relatively little atten-tion in the field of natural language processing(NLP),especially in current var-ious neural network models.In this paper,we investigate three end-to-end neu-ral models for Tibetan text classification.The experimental results show that the end-to-end models outperform the traditional Tibetan text classification meth-ods.The dataset and codes are availabel on https://github.com/FudanNLP/Tibetan-Classification.

作者: Nuo Qun Xing Li Xipeng Qiu Xuanjing Huang

作者单位: School of Computer Science,Fudan University,825 Zhangheng Road,Shanghai,China;School of Information School of Computer Science,Fudan University,825 Zhangheng Road,Shanghai,China

会议类型: 国内会议

会议名称: 第十六届全国计算语言学学术会议暨第五届基于自然标注大数据的自然语言处理国际学术研讨会

会议地点: 南京

会议语种:英文

页码: 1-8

在线出版日期: 2017-10-13（万方平台首次上网日期，不代表论文的发表时间）