Computer Science ›› 2016, Vol. 43 ›› Issue (9): 103-106.doi: 10.11896/j.issn.1002-137X.2016.09.019

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Research on Semi-supervised Learning Based Approach for Lao Part of Speech Tagging

YANG Bei, ZHOU Lan-jiang, YU Zheng-tao and LIU Li-jia   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Aiming at the problem of very few corpora resources,a semi-supervised learning based approach for Lao part of speech Tagging was presented.Firstly,a simple probability model is used to obtain a complete dictionary with a small amount of tagged dictionary and untagged corpus,then much more automatically tagged corpus with integer programming are obtained.Finally,a second-order Markov model with sufficient corpus resources is trained to realize a high quality Lao part of speech tagging.This method achieves a good result in Lao part of speech tagging,and its accuracy is up to 89.8%.

Key words: Semi-supervised learning,Second-order hidden markov model,Lao part of speech tagging,Probability model,Integer programming

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