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A Novel Method for Resolving and Completing Authors'''' Country Affiliation Data in Bibliographic Records

机译:解决和完成书目记录中作者国家联系数据的新方法

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摘要

Purpose: Our work seeks to overcome data quality issues related to incomplete author affiliation data in bibliographic records in order to support accurate and reliable measurement of international research collaboration(IRC).Design/methodology/approch: We propose, implement, and evaluate a method that leverages the Web-based knowledge graph Wikidata to resolve publication affiliation data to particular countries. The method is tested with general and domain-specific data sets.Findings: Our evaluation covers the magnitude of improvement, accuracy, and consistency. Results suggest the method is beneficial, reliable, and consistent, and thus a viable and improved approach to measuring IRC.Research limitations: Though our evaluation suggests the method works with both general and domain-specific bibliographic data sets, it may perform differently with data sets not tested here. Further limitations stem from the use of the R programming language and R libraries for country identification as well as imbalanced data coverage and quality in Wikidata that may also change over time.Practical implications: The new method helps to increase the accuracy in IRC studies and provides a basis for further development into a general tool that enriches bibliographic data using the Wikidata knowledge graph.Originality: This is the first attempt to enrich bibliographic data using a peer-produced, Webbased knowledge graph like Wikidata.
机译:目的:我们的工作寻求克服书目记录中不完整作者隶属关系相关的数据质量问题,以支持准确可靠的国际研究协作测量(IRC).Design /方法/批准:我们提出,实施和评估方法这利用基于Web的知识图形Wikidata将公开隶属数据解析为特定国家。该方法用一般和域特定的数据集进行测试.Findings:我们的评估涵盖了提高,准确性和一致性的幅度。结果表明该方法是有益的,可靠的和一致的,因此是一种测量IRC的可行和改进的方法。虽然我们的评估表明该方法与一般和特定于域的书目数据集一起工作,但它可能与数据不同在这里没有测试。进一步的限制源于使用R编程语言和R库进行国家身份证明,以及Wikidata的不平衡数据覆盖和质量,这些内容也可能随时间而变化。致力解的含义:新方法有助于提高IRC研究的准确性并提供进一步开发成一般工具的基础,用于使用Wikidata知识图形丰富书目数据。这是第一次尝试使用像Wikidata这样的同行制作的Webdraed知识图来丰富书目数据。

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