A Method for Eliminating Articles by Homonymous Authors From the Large Number of Articles Retrieved by Author Search
A Method for Eliminating Articles by Homonymous Authors From the Large Number of Articles Retrieved by Author Search
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DOI：
10.1002/asi.21491
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发表时间：
2011-04-01
影响因子：
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通讯作者：
Yamazaki, Shizuka
中科院分区：
文献类型：
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作者：
Onodera, Natsuo;Iwasawa, Mariko;Yamazaki, Shizuka
本文提出了一种区分目标作者的文章（“真”文章）和其他同名作者的文章（“假”文章）的方法。作者姓名搜索六个主题领域的2595名“源”作者，检索到大约62.9万篇文章。为了从大量的检索文章中提取出真实的文章，包括许多虚假的文章，采用了两个过滤阶段。在第一阶段，如果任何检索到的文章的隶属关系地址与其源文章的地址几乎没有相似之处，或者检索到的文章的期刊与其源文章的期刊之间没有引用关系，则将其作为虚假文章排除。第二阶段，对检索到的文章样本进行人工判断，利用判断结果定义基于逻辑回归的判别函数。这些判别函数的查全率和查准率均在95%左右，正确率（答对率）在90-95%之间。共同作者的存在性、地址相似度、标题词相似度和被检索文章与源文章之间的期刊间引用关系被发现是有效的判别预测因子。来源作者是否来自特定国家也是重要的预测因素之一。此外，研究表明，如果一篇检索到的文章被其源文章引用或共同引用，那么它几乎肯定是正确的。本研究提出的方法在处理大量主题领域和隶属关系地址差异很大的文章时是有效的。
This paper proposes a methodology which discriminates the articles by the target authors ("true" articles) from those by other homonymous authors ("false" articles). Author name searches for 2,595 "source" authors in six subject fields retrieved about 629,000 articles. In order to extract true articles from the large amount of the retrieved articles, including many false ones, two filtering stages were applied. At the first stage any retrieved article was eliminated as false if either its affiliation addresses had little similarity to those of its source article or there was no citation relationship between the journal of the retrieved article and that of its source article. At the second stage, a sample of retrieved articles was subjected to manual judgment, and utilizing the judgment results, discrimination functions based on logistic regression were defined. These discrimination functions demonstrated both the recall ratio and the precision of about 95% and the accuracy (correct answer ratio) of 90-95%. Existence of common coauthor(s), address similarity, title words similarity, and interjournal citation relationships between the retrieved and source articles were found to be the effective discrimination predictors. Whether or not the source author was from a specific country was also one of the important predictors. Furthermore, it was shown that a retrieved article is almost certainly true if it was cited by, or cocited with, its source article. The method proposed in this study would be effective when dealing with a large number of articles whose subject fields and affiliation addresses vary widely.