CHINESE CHUNKING ALGORITHM BASED ON CONDITIONAL RANDOM FIELDS

摘要：

A new Chinese chunking algorithm is proposed based on conditional random fields and semantic features. Through the analysis of Chinese chunking task and its sequential characteristics, conditional random fields that combine various kinds of features were applied. Semantic features were utilized to further improve the chunking performance. Experimental results on the Chinese chunking corpus of Microsoft Research Asia show that the algorithm achieves impressive accuracy of 92.52％ in terms of the F-score.

关键词： Conditional random fields Chinese chunking Semantic features

作者: GUANG-LU SUN BING-QUAN LIU XIAO-LONG WANG YUAN-CHAO LIU

作者单位: School of Computer Science and Technology, Harbin Institute of Technology, 150001, Harbin, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 2509-2513

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）