期刊
JOURNAL OF INFORMETRICS
卷 7, 期 4, 页码 767-773出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.joi.2013.06.006
关键词
Author name disambiguation; Simulation
There are a number of solutions that perform unsupervised name disambiguation based on the similarity of bibliographic records or common coauthorship patterns. Whether the use of these advanced methods, which are often difficult to implement, is warranted depends on whether the accuracy of the most basic disambiguation methods, which only use the author's last name and initials, is sufficient for a particular purpose. We derive realistic estimates for the accuracy of simple, initials-based methods using simulated bibliographic datasets in which the true identities of authors are known. Based on the simulations in five diverse disciplines we find that the first initial method already correctly identifies 97% of authors. An alternative simple method, which takes all initials into account, is typically two times less accurate, except in certain datasets that can be identified by applying a simple criterion. Finally, we introduce a new name-based method that combines the features of first initial and all initials methods by implicitly taking into account the last name frequency and the size of the dataset. This hybrid method reduces the fraction of incorrectly identified authors by 10-30% over the first initial method. (C) 2013 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据