Deep Learning Based Document Theme Analysis for Composition Generation

摘要：

　　This paper puts forward theme analysis problem in order to automatically solve composition writing questions in Chinese college entrance examination.Theme analysis is to distillate the embedded se-mantic information from the given materials or documents.We proposes a hierarchical neural network framework to address this problem.Two deep learning based models under the proposed framework are presented.Besides,two transfer learning strategies based on the proposed deep learning models are tried to deal with the lack of large training data for composition theme analysis problems.Experimental results on two tag recommendation data sets show the effect of the proposed deep learning based theme analysis models.Also,we show the effect of the proposed model with transfer learning on a composition writing questions data set built by ourself.

关键词： theme analysis deep learning transfer learning

作者: Jiahao Liu Chengjie Sun Bing Qin

作者单位: Harbin Institute of Technology,Harbin,China 150001

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: 1-10

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）