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Content aware citation recommendation system

机译:内容意识引文推荐系统

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摘要

Citation Recommendation is very interesting research area. Many algorithms and methods are proposed for better citation recommendation. Recently, the growth of information technology is high. So the digital libraries are there such as IEEE Xplore and ACM Digital library. The online publications of research papers and conferences are increasing day by day. This makes citation recommendation is a very challenging one. In this paper, propose a citation recommendation method that uses citation relations and similarity between many other papers. The basic method consists of recommend citations by cross references. If one paper is co-occurred in two or more citing papers, then they are similar to some extent. After that, these citing papers are pairwise compared with their contents to get similarities between them. Here, evaluate the proposed method in real word datasets such as IEEE journals.
机译:引文推荐是一个非常有趣的研究领域。提出了许多算法和方法以获得更好的引文推荐。最近,信息技术的增长很高。因此,那里有数字图书馆,例如IEEE Xplore和ACM数字图书馆。研究论文和会议的在线出版物日益增多。这使得引文推荐是非常具有挑战性的。本文提出了一种引用建议方法,该方法利用了许多其他论文之间的引用关系和相似性。基本方法包括通过交叉引用推荐引用。如果一篇论文同时出现在两篇或两篇以上的引文中,那么它们在某种程度上是相似的。之后,将这些引文与它们的内容进行成对比较,以获得它们之间的相似性。在这里,请在诸如IEEE期刊等实词数据集中评估该方法。

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