Hidden Markov Model（HMM） is a main solution to ambiguities in Chinese segmentation anti POS （part-of-speech） tagging. While most previous works tot HMM-based Chinese segmentation anti POS tagging eonsult POS infor...Hidden Markov Model（HMM） is a main solution to ambiguities in Chinese segmentation anti POS （part-of-speech） tagging. While most previous works tot HMM-based Chinese segmentation anti POS tagging eonsult POS informatiou in contexts, they do not utilize lexieal information which is crucial for resoMng certain morphologieal ambiguity. This paper proposes a method which incorporates lexieal information and wider context information into HMM. Model induction anti related smoothing technique are presented in detail. Experiments indicate that this technique improves the segmentation and tagging accuracy by nearly 1%.展开更多
基金国家高技术研究发展计划(863计划)，the National Natural Science Foundation of China
文摘Hidden Markov Model（HMM） is a main solution to ambiguities in Chinese segmentation anti POS （part-of-speech） tagging. While most previous works tot HMM-based Chinese segmentation anti POS tagging eonsult POS informatiou in contexts, they do not utilize lexieal information which is crucial for resoMng certain morphologieal ambiguity. This paper proposes a method which incorporates lexieal information and wider context information into HMM. Model induction anti related smoothing technique are presented in detail. Experiments indicate that this technique improves the segmentation and tagging accuracy by nearly 1%.
