Tampa Bay Regional Campus Library, Nova Southeastern University, Clearwater, Florida, USA.
Med Ref Serv Q. 2021 Jul-Sep;40(3):329-336. doi: 10.1080/02763869.2021.1945869.
The explosive growth of digital information in recent years has amplified the information overload experienced by today's health-care professionals. In particular, the wide variety of unstructured text makes it difficult for researchers to find meaningful data without spending a considerable amount of time reading. Text mining can be used to facilitate better discoverability and analysis, and aid researchers in identifying critical trends and connections. This column will introduce key text-mining terms, recent use cases of biomedical text mining, and current applications for this technology in medical libraries.
近年来，数字信息呈爆炸式增长，这加剧了当今医疗保健专业人员所面临的信息过载问题。特别是，大量的非结构化文本使得研究人员如果不花费大量时间阅读，就很难找到有意义的数据。文本挖掘可用于促进更好的可发现性和分析，并帮助研究人员识别关键趋势和联系。本专栏将介绍文本挖掘的关键术语、生物医学文本挖掘的近期用例，以及该技术在医学图书馆中的当前应用。
