Chinese Maximal Noun Phrase Recognition Based on Mixed Strategy
QIAN Xiaofei1, HOU Min2
1. College of Liberal Arts, Shanghai University, Shanghai 200444, China; 2. Broadcast Media Language Branch, National Language Resources Monitoring and Research Center, Communication University of China,Beijing 100024, China
Abstract：This paper proposed a classifier ensemble method based on the language evaluation, and fused the MNP recognition results of SVMs and cascade CRFs based on reduction method, using the automatically obtained collocations and the manual assess rules. It then further targeted recognized the error-prone structures of the classifiers based on deterministic rules. The methods improve the recognition ability of boundary ambiguities of continuous verbs and prepositions as well as continuous nouns. The experiment is successful with a precision rate of 89.30% and a recall rate of 89.62%, especially it improves F1-score of multi-words MNPs by 0.75% in contrast with the reduction method. Key wordsmaximal noun phrase recognition; language knowledge assess; classifier ensemble; rule
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2013, Vol. 27 
