Research on Methods of Semantic Disambiguation about Natural Language Processing

被引：1

作者：

Lou Guohuan ^{[1
]}

Zhang Hao ^{[1
]}

Wang Honghui ^{[1
]}

机构：

[1] Hebei Polytech Univ, Coll Comp & Automat Control, Tangshan, Hebei, Peoples R China

来源：

PROCEEDINGS OF THE 2009 INTERNATIONAL CONFERENCE ON WIRELESS NETWORKS AND INFORMATION SYSTEMS | 2009年

关键词：

natural language processing; Bayesian Model; semantic disambiguation; Hidden Markov Model; Maximum Entropy Model;

D O I：

10.1109/WNIS.2009.21

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Natural language processing is one of the most important applications in artificial intelligence (AI), while semantic disambiguation is one of branches and difficulties in natural language processing. This paper introduces three semantic disambiguation models, Bayesian Model, Hidden Markov Model, and Maximum Entropy Model. These three models are used to test and compare with. The results show that the correct rate of disambiguation used by Bayesian Model is the best one, the other two are also well. Every model has its own advantages.

引用

页码：347 / 349

页数：3