A Feature-Rich CRF Segmenter for Chinese Micro-blog

摘要：

　　This paper describes our system for Chinese word segmentation of micro-blog text,one of the NLPCC-ICCPOL 2016 Shared Tasks 1.The CRF(Conditional Random Field)model is employed to model word segmentation as a sequence labeling problem,7 sets of features are selected to train the CRF model.The system achieves fb 0.798144 on closed track,0.81968 on semi-open track,and 0.82217 on open track with weighted measures 2.

关键词： Chinese word segmentation on Micro-blog Sequence labeling CRF

作者: Yabin Leng Weiwei Liu Sheng Wang Xiaojie Wang

作者单位: School of Computer Science,Beijing University of Posts and Telecommunications,China,100876

会议类型: 国际会议

会议名称: 第五届自然语言处理与中文计算会议(NLPCC-ICCPOL2016)

会议地点: 昆明

会议语种:英文

页码: 1-8

在线出版日期: 2016-12-02（万方平台首次上网日期，不代表论文的发表时间）