Feature engineering for Chinese part-of-speech tagging
Yu Zhengtao · Journal of Shandong University · 2011
Context features have a major impact on the performance of Chinese part-of-speech tagging.In order to improve the performance,the feature engineering for Chinese part-of-speech tagging was explored by the using maximum entropy model.Two key issues of feature engineering,the size of the feature window and the feature templates,were studied.Closed evaluations were performed on PKU,NCC and CTB corpus from the Bakeoff-2007.Then,comparative experiments about the training process and tagging accuracy for Chinese part-of-speech tagging were performed on different feature windows,the and feature windows,and different feature templates: single-word,double-word and mixing feature templates.Experimental results showed that the feature window including 3 words was better than that of 5 words,and the performance increased 10% using single-word feature templates than double-word feature templates.All the results showed that the feature window including 3 words and single-word feature templates were appropriate for Chinese part-of-speech tagging.