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Claper: Recommend Classical Papers to Beginners

机译:块:向初学者推荐古典论文

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Classical papers are of great help for beginners to get familiar with a new research area. However, digging them out is a difficult problem. This paper proposes Claper, a novel academic recommendation system based on two proven principles: the Principle of Download Persistence and the Principle of Citation Approaching (we prove them based on real-world datasets). The principle of download persistence indicates that classical papers have few decreasing download frequencies since they were published. The principle of citation approaching indicates that a paper which cites a classical paper is likely to cite citations of that classical paper. Our experimental results based on large-scale real-world datasets illustrate Claper can effectively recommend classical papers of high quality to beginners and thus help them enter their research areas.
机译:古典论文对于初学者来说,熟悉一个新的研究区域。但是,挖掘它们是一个难题。本文提出了一种基于两项经过两项经过两项验证原则的新型学术推荐系统:下载持久性原则以及引文接近原则(我们以真实世界数据集证明它们)。下载持久性原则表明,自从出版以来,古典论文几乎没有下载频率。引文接近的原则表明,一篇文章的纸张可能引用该古典纸张的引文。我们基于大型现实世界数据集的实验结果说明了Claper可以有效地向初学者提供高质量的古典论文,从而帮助他们进入他们的研究领域。

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