Development and evaluation of task-specific NLP framework in China.
Natural language processing (NLP) has been designed to convert narrative text into structured data. Although some general NLP architectures have been developed, a task-specific NLP framework to facilitate the effective use of data is still a challenge in lexical resource limited regions, such as China. The purpose of this study is to design and develop a task-specific NLP framework to extract targeted information from particular documents by adopting dedicated algorithms on current limited lexical resources. In this framework, a shared and evolving ontology mechanism was designed. The result has shown that such a free text driven platform will accelerate the NLP technology acceptance in China.
College of Biomedical Engineering and Instrument Science, Zhejiang University, The Key Laboratory of Biomedical Engineering, Ministry of Education, Hangzhou, China.
Caixia
C
Ge
College of Biomedical Engineering and Instrument Science, Zhejiang University, The Key Laboratory of Biomedical Engineering, Ministry of Education, Hangzhou, China.
Yinsheng
Y
Zhang
College of Biomedical Engineering and Instrument Science, Zhejiang University, The Key Laboratory of Biomedical Engineering, Ministry of Education, Hangzhou, China.
Zhenzhen
Z
Huang
College of Biomedical Engineering and Instrument Science, Zhejiang University, The Key Laboratory of Biomedical Engineering, Ministry of Education, Hangzhou, China.
Zheng
Z
Jia
College of Biomedical Engineering and Instrument Science, Zhejiang University, The Key Laboratory of Biomedical Engineering, Ministry of Education, Hangzhou, China.
Meizhi
M
Ju
College of Biomedical Engineering and Instrument Science, Zhejiang University, The Key Laboratory of Biomedical Engineering, Ministry of Education, Hangzhou, China.
Huilong
H
Duan
The Children's Hospital of Zhejiang University School of Medicine, Hangzhou, China.
Haomin
H
Li
D064229:Biological Ontologies; D002681:China; D057225:Data Mining / Q000379:methods*; D057286:Electronic Health Records / Q000145:classification*; D000069550:Machine Learning; D009323:Natural Language Processing; D009626:Terminology as Topic; D018875:Vocabulary, Controlled