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基于引文的科学文献新型检索方法:一项验证研究。

Novel citation-based search method for scientific literature: a validation study.

机构信息

Department of Epidemiology, Rollins School of Public Health, Emory University, 1518 Clifton Road NE, Atlanta, GA, 30322, USA.

Woodruff Health Sciences Center Library, Emory University, Atlanta, GA, USA.

出版信息

BMC Med Res Methodol. 2020 Feb 7;20(1):25. doi: 10.1186/s12874-020-0907-5.

DOI:10.1186/s12874-020-0907-5
PMID:32028894
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7006380/
Abstract

BACKGROUND

We recently developed CoCites, a citation-based search method that is designed to be more efficient than traditional keyword-based methods. The method begins with identification of one or more highly relevant publications (query articles) and consists of two searches: the co-citation search, which ranks publications on their co-citation frequency with the query articles, and the citation search, which ranks publications on frequency of all citations that cite or are cited by the query articles.

METHODS

We aimed to reproduce the literature searches of published systematic reviews and meta-analyses and assess whether CoCites retrieves all eligible articles while screening fewer titles.

RESULTS

A total of 250 reviews were included. CoCites retrieved a median of 75% of the articles that were included in the original reviews. The percentage of retrieved articles was higher (88%) when the query articles were cited more frequently and when they had more overlap in their citations. Applying CoCites to only the highest-cited article yielded similar results. The co-citation and citation searches combined were more efficient when the review authors had screened more than 500 titles, but not when they had screened less.

CONCLUSIONS

CoCites is an efficient and accurate method for finding relevant related articles. The method uses the expert knowledge of authors to rank related articles, does not depend on keyword selection and requires no special expertise to build search queries. The method is transparent and reproducible.

摘要

背景

我们最近开发了 CoCites,这是一种基于引文的搜索方法,旨在比传统的基于关键词的方法更高效。该方法从确定一个或多个高度相关的文献(查询文章)开始,包括两个搜索:共引搜索,根据与查询文章的共引频率对文献进行排名;引文搜索,根据引用或被查询文章引用的所有引文的频率对文献进行排名。

方法

我们旨在重现已发表的系统评价和荟萃分析的文献检索,并评估 CoCites 是否在筛选较少标题的同时检索到所有合格的文章。

结果

共纳入 250 篇综述。CoCites 检索到原始综述中包含的文章中位数为 75%。当查询文章被引用更频繁且它们的引文有更多重叠时,检索到的文章比例更高(88%)。仅应用 CoCites 检索到的最高被引文章也得到了类似的结果。当综述作者筛选了超过 500 个标题时,共引和引文搜索的组合更有效,但筛选较少时则不然。

结论

CoCites 是一种高效、准确的方法,用于查找相关的相关文章。该方法利用作者的专业知识对相关文章进行排名,不依赖于关键词选择,也不需要专门的专业知识来构建搜索查询。该方法是透明且可重现的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fd9/7006380/a926f39390ee/12874_2020_907_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fd9/7006380/403af8a1705c/12874_2020_907_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fd9/7006380/d18d2c0f6af5/12874_2020_907_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fd9/7006380/a926f39390ee/12874_2020_907_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fd9/7006380/403af8a1705c/12874_2020_907_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fd9/7006380/d18d2c0f6af5/12874_2020_907_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3fd9/7006380/a926f39390ee/12874_2020_907_Fig3_HTML.jpg

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