会议专题

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

The Third International Conference on Rough Sets and Knowledge Tevhnology(RSKT 2008)(第三届粗糙集与知识技术国际会议)

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)