论文标题
自动生成科学论文的评论
Automatic generation of reviews of scientific papers
论文作者
论文摘要
每年都会发表大量的科学论文，研究人员探索他们已经不熟悉的领域变得更加困难。这极大地抑制了跨学科研究的潜力。传统对一个区域的介绍可能以审查论文的形式出现。但是，并非所有领域和亚地区都有当前的审查。在本文中，我们提出了一种自动生成与用户定义查询相对应的评论论文的方法。该方法由两个主要部分组成。第一部分通过其文献计量参数（例如共插图图）来识别该区域中的关键论文。第二阶段使用基于BERT的体系结构，我们对现有评论进行培训，以提取这些关键论文的摘要。我们描述了我们的方法的一般管道以及一些实施细节，并在PubMed数据集上介绍了自动和专家评估。
With an ever-increasing number of scientific papers published each year, it becomes more difficult for researchers to explore a field that they are not closely familiar with already. This greatly inhibits the potential for cross-disciplinary research. A traditional introduction into an area may come in the form of a review paper. However, not all areas and sub-areas have a current review. In this paper, we present a method for the automatic generation of a review paper corresponding to a user-defined query. This method consists of two main parts. The first part identifies key papers in the area by their bibliometric parameters, such as a graph of co-citations. The second stage uses a BERT based architecture that we train on existing reviews for extractive summarization of these key papers. We describe the general pipeline of our method and some implementation details and present both automatic and expert evaluations on the PubMed dataset.
