Networks of scientific publications play a fundamental role in the search for relevant papers to a specific research topic, as well as in finding authors with expertise in different branches of study. Making a selection of the most important references of a specific paper to understand the evolution of a branch of study is an essential task in the academic world. A challenge for the scientific community has been to identify possible authors relevant to a target paper, for example, to select them as potential reviewers. A solution to find potential expert candidates can be based on the network of citations and on how relevant the authors of selecting papers are in relation to the target paper. With the motivation for developing interactive visual software that helps both researchers and editorial committees, in this paper we present RelPath, a system to help with the task of finding relevant papers and authors for a selected paper. RelPath includes the submission paper in a citations network and establishes relevance of the edges in the network, through which it is possible to build branches of studies and establish a ranking of authors. In this work, we introduce an index to quantify the expertise of the authors by citation paths and we propose a collaborative method to ranking references.

科学出版物网络在寻找针对特定研究主题的相关论文以及寻找在不同研究领域具有专长的作者方面发挥着根本作用。选择特定论文的最重要参考文献以了解研究分支的发展是学术界的一项重要任务。科学界面临的挑战是确定与目标论文相关的可能作者，例如，选择他们作为潜在的审稿人。找到潜在的专家候选人的解决方案可以基于引用网络以及选择论文的作者与目标论文之间的相关性。出于开发对研究人员和编辑委员会都有帮助的交互式视觉软件的动机，在本文中，我们介绍了RelPath，一个系统，可以帮助您找到选定论文的相关论文和作者。RelPath将投稿论文包含在引文网络中，并确定网络边缘的相关性，从而有可能建立研究分支并确定作者排名。在这项工作中，我们引入了一个索引，以通过引文路径量化作者的专业知识，并提出了一种协作方法来对参考文献进行排名。