论文标题

phocus:从一群引用的海洋中挑选有价值的研究

Phocus: Picking Valuable Research from a Sea of Citations

论文作者

Zhang, Xinrong, Ren, Zihou, Li, Xi, Liu, Shuqi, Deng, Yunlong, Xiao, Yadi, Han, Yuxing, Wen, Jiangtao

论文摘要

新论文的洪水极大地阻止了学者的发展,这主要是由仅关注数量的作者级和出版级评估指标引起的。这些指标导致了几个严重的问题,这些问题很长时间以来一直关注重要的研究方向,甚至促进了浮躁的学术氛围。为了解决这些问题,我们提出了Phocus,这是作者和论文的新型学术评估机制。 Phocus分析了包含引文及其上下文的句子,以预测相应参考的情感。将其他因素结合起来,将引用对引用进行了分类,将所有参考文献排在论文中,并利用分类器的结果和排名模型来获取参考论文的局部影响因素。引用论文引用的全球影响因素是局部影响因素的乘积和引用论文的总影响因素。因此,作者的学术影响因素是他对他共同作者的每篇论文的贡献的总和。

The deluge of new papers has significantly blocked the development of academics, which is mainly caused by author-level and publication-level evaluation metrics that only focus on quantity. Those metrics have resulted in several severe problems that trouble scholars focusing on the important research direction for a long time and even promote an impetuous academic atmosphere. To solve those problems, we propose Phocus, a novel academic evaluation mechanism for authors and papers. Phocus analyzes the sentence containing a citation and its contexts to predict the sentiment towards the corresponding reference. Combining others factors, Phocus classifies citations coarsely, ranks all references within a paper, and utilizes the results of the classifier and the ranking model to get the local influential factor of a reference to the citing paper. The global influential factor of the reference to the citing paper is the product of the local influential factor and the total influential factor of the citing paper. Consequently, an author's academic influential factor is the sum of his contributions to each paper he co-authors.

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