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文本挖掘在生物医学领域中的应用文献计量学分析
引用本文:翟兴,唐燕,林琳,郭凤英,刘仁权.文本挖掘在生物医学领域中的应用文献计量学分析[J].现代生物医学进展,2015,15(8):1534-1539.
作者姓名:翟兴  唐燕  林琳  郭凤英  刘仁权
作者单位:北京中医药大学;湖北大学知行学院
基金项目:北京市" 青年英才计划"(YETP0821);北京中医药大学" 青年教师专项计划"(2012-QNJSZX016)
摘    要:目的:近年来,随着生物医学领域文献数量的急骤增长,大量隐含的规律和新知被掩埋在浩如烟海的文献之中,而将文本挖掘技术应用于生物医学领域则可以对海量生物医学文献数据进行整合、分析,从而获得有价值的信息,提高人们对生物医学现象的认识。本文就我国近十年来文本挖掘技术在生物医学领域的应用现状进行文献计量学分析,旨在为我国科研工作者对该领域的进一步研究提供参考。方法:对国内正式发表的生物医学领域文本挖掘相关文献进行检索和筛选,分别从年度变化、地区分布、研究机构、期刊来源、研究领域等方面进行分析。结果:国内生物医学文本挖掘文献总量呈上升趋势,主要集中在挖掘算法的研究和文本挖掘技术在中医药及系统生物学领域的应用方面;北京、上海、广东等地的研究处于领先地位。结论:相比其他较为成熟的研究课题来说,目前文本挖掘技术在生物医学中的应用在国内还属于一个比较新的研究领域,但国内对该领域的认识正不断提高、研究正不断深入,初步形成了一批在该领域的核心研究地区、核心研究机构和核心研究领域,而对其进一步的研究,必将为生物医学领域的发展注入新的活力。

关 键 词:文本挖掘  生物医学  发展趋势  文献计量学

Bibliometrics Analysis on Text Mining in Bomedical Field
Abstract:Objective:In recent years, with the rapid growth of biomedical literature, a lot of hidden rules and new knowledge buried in it. The text mining technology used in the biomedical field can be integrated and analyzed on massive biomedical literature, so as to obtain valuable information and raise awareness of biomedical. In this research, bibliometric method will be used to analyze text mining in biomedical field in China from 2004 to 2013, in order to provide references for the further study.Methods:Corresponding text mining references in the biomedical field, which had been published formally in China, had been searched and selected, respectively from the annual changes, regional distribution, research institutions, source journals and research fields.Results:Biomedical text mining literature of China overall upward trend, mainly concentrated in the application of data mining algorithm and text mining technology in the field of TCMand systems biology. Beijing, Shanghai and Guangdong were in the leading position.Conclusion:Compared with other mature research subject, the text mining technology in biomedicine is a new territory in China. But the domestic research on it is constantly improving and a number of core research areas, institutions and direction are initially formed. The deep study of it will inject new vitality in the development of the biomedical field.
Keywords:Text mining  Biomedical  Development trends  Bibliometrics
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