| Title |
Investigating Domain Features For Scope Detection and Classification of Scientific Articles |
| Authors |
Tirthankar Ghosal, Ravi Sonam, Sriparna Saha, Asif Ekbal, Pushpak Bhattacharyya |
| Abstract |
Editorial screening or better known as Desk Rejection is a common phenomena in scholarly publishing. Many papers suffer Desk Rejection simply because they are not sent to the right journal. We propose a supervised machine learning system that could assist the editors in identifying out-of-scope manuscripts. Our approach is simple and learns feature representation from different sections of a research paper that contributes in adjudging the domain of the paper. On a certain journal our system outperforms the state-of-the-art by a wide margin (~37% in terms of accuracy). We believe that our approach is generic and with suitable adjustments could be applied to other journals having well-defined scope. Our feature set displays further potential for the development of a better journal recommender system for academic manuscripts. |
Full paper |
Investigating Domain Features For Scope Detection and Classification of Scientific Articles
|
| Bibtex |
@InProceedings{GHOSAL18.12,
author = {Tirthankar Ghosal ,Ravi Sonam ,Sriparna Saha ,Asif Ekbal and Pushpak Bhattacharyya},
title = {Investigating Domain Features For Scope Detection and Classification of Scientific Articles},
booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)},
year = {2018},
month = {may},
date = {7-12},
location = {Miyazaki, Japan},
editor = {},
publisher = {European Language Resources Association (ELRA)},
address = {Paris, France},
isbn = {979-10-95546-20-7},
language = {english}
} |
Summary of the paper