Chinese Term Recognition Based on Hidden Markov Model
基于隐马尔科夫模型的中文术语识别研究

After a perceptive analysis of probabilistic characteristics of syntax composition especially POS matching of Chinese textual information,a system framework for Chinese term recognition and extraction based on dual layer HMM is presented and implemented.The method proposed shows a good performance in the tests with textual information from different domain,and the terms recognized and extracted by the implemented system can be treated as candidate terms for false-eliminating and optimizing combining with parameters of mutual information,log likelihood and domain dependency.