Application of Bayesian decision tree to recognition of English present participle
Xun Liu · Journal of Computer Applications · 2009
Concerning the difficulties in part-of-speech tagging in English present participle,the authors analyzed the drawbacks of Hidden Markov Models(HMM)and proposed Bayesian decision tree model.Firstly,the tagged corpus was calculated and C4.5 in decision tree was used for proper classification and disambiguation of the three classes of present participle.Then,the decision tree was improved by Bayesian least risk.At last,an untagged corpus was used to test the model and the result is very good,which proves the superiority of the model.