An Enhanced Model for Chinese Word Segmentation and Part-of-Speech Tagging
Feng Jiang, Hui Liu, Yuquan Chen, LU Ru-zhan · Meeting of the Association for Computational Linguistics · 2004
This paper will present an enhanced probabilistic model for Chinese word segmentation and part-of-speech (POS) tagging. The model introduces the information of Chinese word length as one of its features to reach a more accurate result. And in addition, the model also achieves the integration of segmentation and POS tagging. After presenting the model, this paper will give a brief discussion on how to solve the problems in statistics and how to further integrate Chinese Named Entity Recognition into the model. Finally, some figures of experiments and comparisons will be reported, which shows that the accuracy of word segmentation is 97.09%, and the accuracy of POS tagging is 98.77%.