论文标题
引用建议:方法和数据集
Citation Recommendation: Approaches and Datasets
论文作者
论文摘要
引文建议描述了推荐给定文本的引用的任务。一方面,由于近年来已发表的科学作品超负荷,并且在撰写科学文本时需要引用最合适的出版物,因此引用建议已成为一个重要的研究主题。近年来,已经提出了几种方法和评估数据集。但是,据我们所知,没有根据引用建议明确进行文献调查。在本文中,我们对自动引文推荐研究进行了详尽的介绍。然后,我们概述了引用建议的方法和数据集,并使用各种维度确定差异和共同点。最后但并非最不重要的一点是,我们阐明了评估方法,并概述了评估中的一般挑战以及如何满足它们。我们将自己限制在科学出版物的引用建议中,因为该文档类型在该领域中的研究最多。但是,本调查中包括的许多观察和讨论也适用于其他类型的文本,例如新闻文章和百科全书文章。
Citation recommendation describes the task of recommending citations for a given text. Due to the overload of published scientific works in recent years on the one hand, and the need to cite the most appropriate publications when writing scientific texts on the other hand, citation recommendation has emerged as an important research topic. In recent years, several approaches and evaluation data sets have been presented. However, to the best of our knowledge, no literature survey has been conducted explicitly on citation recommendation. In this article, we give a thorough introduction into automatic citation recommendation research. We then present an overview of the approaches and data sets for citation recommendation and identify differences and commonalities using various dimensions. Last but not least, we shed light on the evaluation methods, and outline general challenges in the evaluation and how to meet them. We restrict ourselves to citation recommendation for scientific publications, as this document type has been studied the most in this area. However, many of the observations and discussions included in this survey are also applicable to other types of text, such as news articles and encyclopedic articles.