论文标题
科学论文推荐系统：最新出版物的文献综述
Scientific Paper Recommendation Systems: a Literature Review of recent Publications
论文作者
论文摘要
科学写作以已经发表的论文为基础。手动识别出版物要阅读，引用或考虑相关论文的出版物取决于研究人员识别可以启动文献搜索的合适关键字或初始论文的能力。迅速增加的论文呼吁采取自动措施，以找到所需的相关出版物，即所谓的纸质建议系统。 随着出版物数量的增加，纸张推荐系统的数量也随之增加。以前的文献评论着重于讨论多年来的一般方法，并突出了主要方向。我们从这个角度避免使用，相反，我们仅考虑一个相对较小的时间范围，但可以完全分析。 在本文献综述中，我们讨论了在2019年1月至2021年10月之间首次发布的所有作品中遇到的方法，数据集，评估和公开挑战。该调查的目的是提供当前论文建议系统的全面，完整的概述。
Scientific writing builds upon already published papers. Manual identification of publications to read, cite or consider as related papers relies on a researcher's ability to identify fitting keywords or initial papers from which a literature search can be started. The rapidly increasing amount of papers has called for automatic measures to find the desired relevant publications, so-called paper recommendation systems. As the number of publications increases so does the amount of paper recommendation systems. Former literature reviews focused on discussing the general landscape of approaches throughout the years and highlight the main directions. We refrain from this perspective, instead we only consider a comparatively small time frame but analyse it fully. In this literature review we discuss used methods, datasets, evaluations and open challenges encountered in all works first released between January 2019 and October 2021. The goal of this survey is to provide a comprehensive and complete overview of current paper recommendation systems.
