Shallow Parsing of Chinese Based on HMM Model

被引：0

作者：

Zheng Weifa ^{[1
]}

Xie Wenliang ^{[1
]}

机构：

[1] Guangdong Univ Business Studies, Informat Off, Guangzhou 510320, Peoples R China

来源：

INTELLIGENCE COMPUTATION AND EVOLUTIONARY COMPUTATION | 2013年 / 180卷

关键词：

HMM; Shallow Parsing; Natural Language Processing;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Complete parsing is difficult to meet the need of. precision and recall rate in Chinese. To address this problem, a new model for shallow parsing of Chinese is presented in this paper. We adopt Church theory and carry on Chinese phrases recognition based on HMM; improve the precision rate of sentences separation by improving the observance probabilities of HMM model and making use of the context information of the Chinese sentences. At the same time, by studying the rules of Chinese sentence, we extract some rules useful for ambiguity elimination. The experimental result indicates that the model based on HMM has high precision and recall rate.

引用

页码：79 / 86

页数：8

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