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基于 4P 医学术语动态的知识演化追踪。

Tracking Knowledge Evolution Based on the Terminology Dynamics in 4P-Medicine.

机构信息

Autonomous Nonprofit Organization, Research Center for Physical and Technical Informatics, Nizhny Novgorod 603098, Russia.

School of Management, Hefei University of Technology, Hefei 230009, China.

出版信息

Int J Environ Res Public Health. 2020 Oct 13;17(20):7444. doi: 10.3390/ijerph17207444.

Abstract

The accelerating evolution of scientific terms connected with 4P-medicine terminology and a need to track this process has led to the development of new methods of analysis and visualization of unstructured information. We built a collection of terms especially extracted from the PubMed database. Statistical analysis showed the temporal dynamics of the formation of derivatives and significant collocations of medical terms. We proposed special linguistic constructs such as megatokens for combining cross-lingual terms into a common semantic field. To build a cyberspace of terms, we used modern visualization technologies. The proposed approaches can help solve the problem of structuring multilingual heterogeneous information. The purpose of the article is to identify trends in the development of terminology in 4P-medicine.

摘要

随着与 4P 医学术语相关的科学术语的加速演变,以及跟踪这一过程的需求,新的分析和可视化非结构化信息的方法得到了发展。我们从 PubMed 数据库中专门提取了术语集。统计分析显示了衍生物形成的时间动态和医学术语的显著搭配。我们提出了特殊的语言结构,如 megatokens,用于将跨语言术语组合到一个共同的语义领域。为了构建术语的网络空间,我们使用了现代可视化技术。所提出的方法可以帮助解决多语言异质信息的结构化问题。本文的目的是确定 4P 医学术语发展的趋势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c27/7600767/764409aba0ba/ijerph-17-07444-g001.jpg

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