Apply a Rough Set-Based Classifier to Dependency Parsing
A rough set-based semi-naive Bayesian classification method is applied to dependency parsing,which is an important task in syntactic structure analysis of natural language processing.Many parsing algorithms have emerged combined with statistical machine learning techniques.The rough set-based classifier is embedded with Nivres deterministic parsing algorithm to conduct dependency parsing task on a Chinese corpus.Experimental results show that the method has a good performance on dependency parsing task.Moreover,the experiments have justified the effectiveness of the classification influence.
Rough set Attribute dependency Semi-naive Bayesian clas-sifter Dependency parsing
Yangsheng Ji Lin Shang Xinyu Dai Ruoce Ma
State Key Laboratory for Novel Software Technology,Nanjing University,China
国际会议
成都
英文
97-105
2008-05-17(万方平台首次上网日期,不代表论文的发表时间)