中国特定任务自然语言处理框架的开发与评估。

Development and evaluation of task-specific NLP framework in China.

作者信息

Ge Caixia, Zhang Yinsheng, Huang Zhenzhen, Jia Zheng, Ju Meizhi, Duan Huilong, Li Haomin

机构信息

College of Biomedical Engineering and Instrument Science, Zhejiang University, The Key Laboratory of Biomedical Engineering, Ministry of Education, Hangzhou, China.

The Children's Hospital of Zhejiang University School of Medicine, Hangzhou, China.

出版信息

Stud Health Technol Inform. 2015;216:1031.

PMID:26262331

Abstract

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.

摘要

自然语言处理（NLP）旨在将叙述性文本转换为结构化数据。尽管已经开发了一些通用的NLP架构，但在词汇资源有限的地区，如中国，开发一个有助于有效利用数据的特定任务NLP框架仍然是一项挑战。本研究的目的是设计和开发一个特定任务的NLP框架，通过在当前有限的词汇资源上采用专用算法，从特定文档中提取目标信息。在这个框架中，设计了一种共享且不断发展的本体机制。结果表明，这样一个由自由文本驱动的平台将加速NLP技术在中国的应用。