预测学术论文接受度的机器学习方法

M. Skorikov, S. Momen
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引用次数: 7

摘要

在这篇论文中,机器学习方法被用来预测一篇科学论文是否会被顶级人工智能会议接受。这将有助于作者确定他们的论文被顶级人工智能会议接受的可能性。我们使用了PeerRead数据集,其中包含从主要人工智能会议收集的论文,这些论文都是公开的。我们使用随机森林分类器实现了81%的准确率。这篇论文的新颖之处在于,它准确地预测了一篇科学论文是否会被人工智能顶级会议接受。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine learning approach to predicting the acceptance of academic papers
In this paper, machine learning approaches have been used to predict whether a scientific paper will be accepted in a top-tier AI conferences or not. This shall help authors identify the likelihood of their paper getting accepted in a top-tier AI conference. We have used the PeerRead dataset containing papers collected from major AI conferences that are publicly available. We have achieved an accuracy of 81% using Random Forest classifier. The novelty of the paper lies in accurately predicting whether a scientific paper will be accepted in the top AI conference.
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