Title :
Chinese part of speech tagging based on maximum entropy method
Author :
Lin, Hong ; Yuan, Chun-fa
Author_Institution :
State Key Lab. of Intelligent Technol. & Syst., Tsinghua Univ., Beijing, China
Abstract :
A lot of researches have been made on the application of the maximum entropy modeling in natural language processing in recent years. In this paper, we present a new Chinese part of speech tagging method based on the maximum entropy principle because Chinese language is quite different from many other languages. The feature selection is the key point in our system, which is distinct from the one used in English. Experiment results show that the part of speech tagging accuracy ratio of our system is up to 97.34%.
Keywords :
grammars; learning (artificial intelligence); maximum entropy methods; natural languages; probability; Chinese language; language model; maximum entropy; natural language processing; part of speech tagging; probability distribution; training set; Application software; Computer science; Databases; Entropy; Hidden Markov models; Intelligent systems; Natural languages; Random processes; Speech processing; Tagging;
Conference_Titel :
Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on
Print_ISBN :
0-7803-7508-4
DOI :
10.1109/ICMLC.2002.1167446
