With the increasing availability of online scholarly databases, publication records can be easily extracted and analysed. Researchers can promptly keep abreast of others’ scientific production and, in principle, can select new collaborators and build new research teams. A critical factor one should consider when contemplating new potential collaborations is the possibility of unambiguously defining the expertise of other researchers. While some organisations have established database systems to enable their members to manually produce a profile, maintaining such systems is time-consuming and costly. Therefore, there has been a growing interest in retrieving expertise through automated approaches. Indeed, the identification of researchers’ expertise is of great value in many applications, such as identifying qualified experts to supervise new researchers, assigning manuscripts to reviewers, and forming a qualified team. Here, we propose a network-based approach to the construction of authors’ expertise profiles. Using the MEDLINE corpus as an example, we show that our method can be applied to a number of widely used data sets and outperforms other methods traditionally used for expertise identification.

随着在线学术数据库可用性的增加，可以轻松提取和分析出版物记录。研究人员可以及时了解他人的科学成果，原则上可以选择新的合作者，组建新的研究团队。在考虑新的潜在合作时应该考虑的一个关键因素是明确定义其他研究人员的专业知识的可能性。虽然一些组织已经建立了数据库系统以使其成员能够手动生成配置文件，但维护此类系统既费时又费钱。因此，人们对通过自动化方法检索专业知识的兴趣日益浓厚。事实上，鉴定研究人员的专业知识在许多应用中具有重要价值，例如确定合格的专家来监督新的研究人员，将稿件分配给审稿人，组建合格的团队。在这里，我们提出了一种基于网络的方法来构建作者的专业知识档案。以 MEDLINE 语料库为例，我们表明我们的方法可以应用于许多广泛使用的数据集，并且优于传统上用于专业知识识别的其他方法。