Analysis and suggestion of double-blind review comments based on NLP technology
Kunli Zhang, Yutuan Ma, Hongying Zan · 2022 Global Conference on Robotics, Artificial Intelligence and Information Technology (GCRAIT) · 2022
The double-blind review dissertation is a key link in strengthening quality supervision and inspection, promoting standardized management of degree awarding, improving internal quality assurance system, and accelerating the high-quality development of postgraduate education in the new era. Experts review the dissertation and put forward revision opinions, which largely reflect the problems existing in the dissertation, and have important reference value for the guidance of graduate dissertation. This paper analyzes the review comments received by computer dissertations through word cloud analysis, text feature extraction and other NLP technologies, summarizing common problems and puts forward corresponding suggestions, so as to provide more targeted reference for the guidance of dissertations.