Study of Kernel-Based Methods for Chinese Relation Extraction

摘要：

In this paper,we mainly explore the effectiveness of two kernelbased methods,the convolution tree kernel and the shortest path dependency kernel,in which parsing information is directly applied to Chinese relation extraction on ACE 2007 corpus.Specifically,we explore the effect of different parse tree spans involved in convolution kernel for relation extraction.Besides,we experiment with composite kernels by combining the convolution kernel with feature-based kernels to study the complementary effects between tree kernel and flat kernels.For the shortest path dependency kernel,we improve it by replacing the strict same length requirement with finding the longest common subsequences between two shortest dependency paths.Experiments show kernel-based methods are effective for Chinese relation extraction.

作者: Ruihong Huang Le Sun Yuanyong Feng

作者单位: Institute of Software,Chinese Academy of Sciences,South Fourth Street,Zhong Guan Cun,Hai Dian.4,1001 Institute of Software,Chinese Academy of Sciences,South Fourth Street,Zhong Guan Cun,Hai Dian.4,1001

会议类型: 国际会议

会议名称: 4th Asia Information Retrieval Symposium(AIRS 2008)(第四届亚洲信息检索研讨会)

会议地点: 哈尔滨

会议语种:英文

页码: 598-604

在线出版日期: 2008-01-16（万方平台首次上网日期，不代表论文的发表时间）