关键词： 最大熵模型, 隐马尔科夫模型, 中文词性标注

Abstract:

In order to further improve the efficiency of part-of-speech tagging in Chinese corpora, experiments of Chinese part-of-speech tagging methods based on the maximum entropy model (MEM) and the hidden Markov model (HMM) are designed according to the theoretical basis, algorithms, and application technology. The experimental results  show that the Chinese part-of-speech tagging algorithms based on MEM and HMM have obtained a very consistent and high-coverage tagging result and the three indicators of tagging accuracy, recall rate and F1 value have reached above 92%, with the effect of MEM  better than that of HMM.

Key words: maximum entropy model, hidden Markov model, Chinese part-of-speech tagging