Tirthankar Ghosal
ABSTRACT
Editorial pre-screening is the first step in academic peer review. The deluge of research papers and the huge amount of submissions being made to journals these days makes editorial decision a very challenging task. The current work attempts to investigate certain impact factors that may have a role in the editorial decision making process. The proposed work exhibits potential for the development of an AI-assisted peer review system which could aid the editors as well as the authors in making appropriate decisions in reasonable time and thus accelerate the overall process of scholarly publishing.
- Yuxiao Dong, Reid A Johnson, and Nitesh V Chawla . 2016. Can scientific impact be predicted? IEEE Transactions on Big Data Vol. 2, 1 (2016), 18--30.Google Scholar
Cross Ref
- Tirthankar Ghosal, Rajeev Verma, Asif Ekbal, Sriparna Saha, and Pushpak Bhattacharyya . 2018. An AI aid to the editors. Exploring the possibility of an AI assisted article classification system. arXiv preprint arXiv:1802.01403 (2018).Google Scholar
- Luca Weihs and Oren Etzioni . 2017. Learning to Predict Citation-Based Impact Measures Digital Libraries (JCDL), 2017 ACM/IEEE Joint Conference on. IEEE, 1--10. Google ScholarDigital Library
Index Terms
- Investigating Impact Features in Editorial Pre-Screening of Research Papers
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