Automatic Academic Paper Rating Based on Modularized Hierarchical Convolutional Neural Network
Pengcheng Yang, Xu Sun, Wei Li, Shuming Ma · 2018
As more and more academic papers are being submitted to conferences and journals, evaluating all these papers by professionals is time-consuming and can cause inequality due to the personal factors of the reviewers.In this paper, in order to assist professionals in evaluating academic papers, we propose a novel task: automatic academic paper rating (AAPR), which automatically determine whether to accept academic papers.We build a new dataset for this task and propose a novel modularized hierarchical convolutional neural network to achieve automatic academic paper rating.Evaluation results show that the proposed model outperforms the baselines by a large margin.The dataset and code are available at https: //github.com/lancopku/AAPR