A Comparison Study of Sequence Labeling Methods for Chinese Word Segmentation,POS Tagging Models
Meishan Zhang · Zhongwen xinxi xuebao · 2013
In this paper,we compare three different Chinese word segmentation and POS tagging models.Accuracy and speed are considered during the comparison.First of these three models are pipelinesequential model.The second is a joint model for word segmentation and POS tagging,andthe last one is a combination of two modelsmentionedabove with a stacked learning framework.We conduct experiments on four data sets,including People Daily,CoNLL09,CTB5.0 and CTB7.0.Experimental results show that the joint model achieves the fastest speed while the stacked learning model achievesthe highest accuracy.Finally,we compare our stacked learning model with state-of-the-art systems on data sets CTB5.0 and CTB7.0 and our model achieve the best performance in this comparison.