数据采集与处理2017，Vol.32Issue(1)：175-181,7.DOI:10.16337/j.1004-9037.2017.01.021
融合语义类信息的句法分析统计模型
Statistical Syntactic Parsing Model Fusing Semantic Category Information
摘要
Abstract
Data sparseness severely affects the system performances of syntactic parsing,and syntactic structures are unities of syntactic forms and semantic contents.Based on the labeling of semantic information,a word clustering model and algorithm is proposed.And a head-driven statistical syntactic parsing model based on semantic category is established.The problem of data sparseness is successfully solved,and the system performances of syntactic parsing are obviously enhanced.Experiments are conducted for the head-driven statistical syntactic parsing model based on semantic category.It achieves 88.73 ％ precision and 88.26 ％ recall.F measure is improved 8.39 ％ compared with the distinctive head-driven parsing model.关键词
句子结构分析统计模型/语义角色标注/词的自动聚类/头驱动Key words
statistical syntactic parsing model/semantic role labeling/word clustering/head-drive分类
信息技术与安全科学引用本文复制引用
袁里驰..融合语义类信息的句法分析统计模型[J].数据采集与处理,2017,32(1):175-181,7.基金项目
国家自然科学基金(61262035,61562034)资助项目 （61262035,61562034）
江西省自然科学基金(20142BAB207028)资助项目 （20142BAB207028）
江西省科技支撑计划(20151BBE50082)资助项目. （20151BBE50082）
