排序方式： 共有28条查询结果，搜索用时 15 毫秒
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ＭeＳＨＡ主题词选设与文献量相关度剖析 总被引：1，自引：0，他引：1
本文调查分析了《医学主题词表 》的变化机制以及主题词选设与文献量之间的相互关系，旨在进一步把握ＭeＳＨ的变化特点，提高医学主题词医学文献检索与标引中的使用效果。结果表明：其一，有两方面的因素影响着ＭeＳＨ词表总量的变化；其二，不同的新增主题词在设立之前所汇集的文献量和文献中出现的频率存在着极大差异。 相似文献
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借鉴Rodriguez和Egenhofer提出的语义相似度计算模型,结合医学领域主题词表MeSH的特点,提出MeSH主题词表中的语义相似度计算方法,实验结果证明该方法是有效的。 相似文献
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Emily Vardell Tanya Feddern-Bekcan Mary Moore 《Medical reference services quarterly》2013,32(3):283-294
SciVal Experts is a resource for finding experts and fostering collaboration. The tool creates researcher profiles with automatically updated publication and grant information and faculty-inputted curriculum vitae, more fully capturing a researcher's body of work. SciVal Experts indexes campus-based “experts” by research topic, allowing faculty to find potential research partners and mentors, furthering translational research opportunities and dissemination of knowledge. 相似文献
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本文尝试分析在非相关文献知识发现中,标题对文摘的替代效果,标题和MeSH提供的信息内容与文摘提供的信息内容的近似度,标题与文摘提供的信息内容与MeSH字段提供的信息内容的近似度.通过统计各字段所有词的词频,从高频词的数量、分布及变化趋势等定量的方面,以及具体高频词和语义类型等定性方面对各字段进行对比分析.结果表明标题对文摘有很好的替代效果,标题与MeSH结合对文摘的替代效果较标题与文摘结合对MeSH的替代效果要好. 相似文献
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Background: Search filters have been developed in MEDLINE and EMBASE to help overcome the challenges of searching electronic databases for information on adverse effects. However, little evaluation of their effectiveness has been carried out. Objectives: To measure the sensitivity and precision of available adverse effects search filters in MEDLINE and EMBASE. Methods: A case study systematic review of fracture related adverse effects associated with the use of thiazolidinediones was used. Twelve MEDLINE search strategies and three EMBASE search strategies were tested. Results: Nineteen relevant references from MEDLINE and 24 from EMBASE were included in the review. Four search filters in MEDLINE achieved high sensitivity (95 or 100%) with an improved level of precision from searches without any adverse effects filter. High precision in MEDLINE could also be achieved (up to 53%) using search filters that rely on Medical Subject Headings. No search filter in EMBASE achieved high precision (all were under 5%) and the highest sensitivity in EMBASE was 83%. Conclusions: Adverse effects search filters appear to be effective in MEDLINE for achieving either high sensitivity or high precision. Search filters in EMBASE, however, do not appear as effective, particularly in improving precision. 相似文献
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本文充分考虑了主题词之间的已知关联和未知关联,利用MeSH词表对已知关联进行了处理,优化了主题结构分析方法,并以属分关系为例,对该方法进行了实证分析.结果表明在阈值一定的前提下,基于MeSH的主题结构分析方法能够有效地剔除词间的已知关联,揭示出相对较微弱的词间未知关联,起到了主题词关系过滤的作用,为知识发现奠定了基础. 相似文献
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孙艳 《中华医学图书馆杂志》2014,(9):75-77
目的：对比分析Embase.com和PubMed的检索结果,为科研人员推荐最适合的检索工具和提高检索效率。方法：选取8个不同学科的检索词,在PubMed和Embase.com中分别采用主题词检索和带有自动转换功能的基本检索两种途径检索。结果：8个检索词在检索中出现6种不同情况。结论：通过主题词检索,总体来说Embase.com检全率要高于PubMed;带有自动转换功能的基本检索,两个数据库都会出现错误转换,但从转换的原理上看,PubMed的查准率更高。 相似文献
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This paper investigates the effectiveness of using MeSH® in PubMed through its automatic query expansion process: Automatic Term Mapping (ATM). We run Boolean searches based on a collection of 55 topics and about 160,000 MEDLINE® citations used in the 2006 and 2007 TREC Genomics Tracks. For each topic, we first automatically construct a query by selecting keywords from the question. Next, each query is expanded by ATM, which assigns different search tags to terms in the query. Three search tags: [MeSH Terms], [Text Words], and [All Fields] are chosen to be studied after expansion because they all make use of the MeSH field of indexed MEDLINE citations. Furthermore, we characterize the two different mechanisms by which the MeSH field is used. Retrieval results using MeSH after expansion are compared to those solely based on the words in MEDLINE title and abstracts. The aggregate retrieval performance is assessed using both F-measure and mean rank precision. Experimental results suggest that query expansion using MeSH in PubMed can generally improve retrieval performance, but the improvement may not affect end PubMed users in realistic situations. 相似文献
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Objective:This study compares two maps of biomedical sciences using Medical Subject Headings (MeSH) term co-assignments versus MeSH terms of citing/cited articles and reveals similarities and differences between the two approaches.Methods:MeSH terms assigned to 397,475 journal articles published in 2015, as well as their 4,632,992 cited references, were retrieved from Web of Science and MEDLINE databases, respectively, which formed over 7 million MeSH co-assignments and nearly 18 million direct citation pairs. We generated six network visualizations of biomedical science at three levels using Gephi software based on these MeSH co-assignments and citation pairs.Results:The MeSH co-assignment map contained more nodes and edges, as MeSH co-assignments cover all medical topics discussed in articles. By contrast, the MeSH citation map contained fewer but larger nodes and wider edges, as citation links indicate connections to two similar medical topics.Conclusion:These two types of maps emphasize different aspects of biomedical sciences, with MeSH co-assignment maps focusing on the relationship between topics in different categories and MeSH direct citation maps providing insights into relationships between topics in the same or similar category. 相似文献