Chinese word sense disambiguation based on hidden Markov model
发表时间：2019-03-11
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论文类型：
期刊论文
第一作者：
Chun-Xiang, Zhang
通讯作者：
Xue-Yao, Gao(gaoxueyao@hrbust.edu.cn)
合写作者：
Yan-Chen, Sun,Xue-Yao, Gao,Zhi-Mao, Lu
发表时间：
2015-01-01
发表刊物：
International Journal of Database Theory and Application
收录刊物：
EI
文献类型：
J
卷号：
8
期号：
6
页面范围：
263-270
ISSN号：
20054270
摘要：
Word sense disambiguation (WSD) is important for natural language processing. It plays important roles in information retrieval, machine translation, text categorization and topic tracking. In this paper, the transition among senses of words is considered. For an ambiguous word, its semantic codes and its left word's semantic codes are taken as disambiguation features. At the same time, a new method based on hidden Markov model (HMM) is proposed for Chinese word sense disambiguation. Chinese Tongyici Cilin is used to determine semantic codes of words. HMM is optimized in training corpus. The WSD classifiers based on HMM is tested. Experimental results show that the accuracy of word sense disambiguation is improved. © 2015 SERSC.
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