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LigerCat:利用来自期刊、文章或基因引用的“医学主题词云”来促进相关生物医学文献的识别。

LigerCat: using "MeSH Clouds" from journal, article, or gene citations to facilitate the identification of relevant biomedical literature.

作者信息

Sarkar Indra Neil, Schenk Ryan, Miller Holly, Norton Catherine N

机构信息

Center for Clinical and Translational Science, University of Vermont, Burlington, VT, USA.

出版信息

AMIA Annu Symp Proc. 2009 Nov 14;2009:563-7.

Abstract

The identification of relevant literature from within large collections is often a challenging endeavor. In the context of indexed resources, such as MEDLINE, it has been shown that keywords from a controlled vocabulary (e.g., MeSH) can be used in combination to retrieve relevant search results. One effective strategy for identifying potential search terms is to examine a collection of documents for frequently occurring terms. In this way, "Tag clouds" are a popular mechanism for ascertaining terms associated with a collection of documents. Here, we present the Literature and Genomic Electronic Resource Catalogue (LigerCat) system for exploring biomedical literature through the selection of terms within a "MeSH cloud" that is generated based on an initial query using journal, article, or gene data. The resultant interface is encapsulated within a Web interface: http://ligercat.ubio.org. The system is also available for installation under an MIT license.

摘要

从大量文献中识别相关文献往往是一项具有挑战性的工作。在诸如MEDLINE等索引资源的背景下,研究表明来自受控词汇表(如医学主题词表)的关键词可以组合使用以检索相关的搜索结果。识别潜在搜索词的一种有效策略是检查一组文档中频繁出现的词汇。通过这种方式,“标签云”是确定与一组文档相关的词汇的常用机制。在这里,我们展示了文献与基因组电子资源目录(LigerCat)系统,该系统通过在基于使用期刊、文章或基因数据的初始查询生成的“医学主题词表云”中选择词汇来探索生物医学文献。生成的界面封装在一个Web界面中:http://ligercat.ubio.org。该系统也可根据麻省理工学院许可进行安装。

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