DocumentCode
3442920
Title
A Method Integrating Rule and HMM for Chinese Part-of-speech Tagging
Author
Ning, Hui ; Yang, Hua ; Li, Zhihui
Author_Institution
Harbin Eng. Univ., Harbin
fYear
2007
fDate
23-25 May 2007
Firstpage
723
Lastpage
725
Abstract
In this paper, we study the lexical category disambiguation and the disambiguation strategy using rule techniques and HMM (hidden Markov model) is introduced. With the above method, a system of disambiguation is materialized. The experimental results show that the tagging accuracy is raised by using rule techniques and hidden Markov model. The disambiguation accuracy of close test and open test is 92.97% and 91.21% respectively, and the overall accuracy is 97.84% and 96.71% respectively.
Keywords
hidden Markov models; natural language processing; speech processing; Chinese part-of-speech tagging; HMM; hidden Markov model; lexical category disambiguation; method integrating rule; natural language processing; Hidden Markov models; Industrial electronics; Tagging;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics and Applications, 2007. ICIEA 2007. 2nd IEEE Conference on
Conference_Location
Harbin
Print_ISBN
978-1-4244-0737-8
Electronic_ISBN
978-1-4244-0737-8
Type
conf
DOI
10.1109/ICIEA.2007.4318501
Filename
4318501
Link To Document