Chinese POS Tagging Using Restricted MaximumEntropy Model
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Graphical Abstract
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Abstract
This paper presents Chinese Part-of-speech
(POS) tagging using maximum entropy technique, in which
we introduce a novel gain-driven method for feature selec-
tion, then we describe the restricted training method for
model learning. We test our approach on the simpli¯ed
Chinese corpus of Peking University China and achieve an
accuracy of 97.80% and 98.60% over ¯ne and coarse grained
tag set - a signi¯cant improvement over the existing Chi-
nese POS tagger.
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