Where to Submit? Helping Researchers to Choose the Right Venue
K. Kobs, T. Koopmann, A. Zehe, D. Fernes, P. Krop, and A. Hotho. Findings of the Association for Computational Linguistics: EMNLP 2020, page 878--883. Online, Association for Computational Linguistics, (November 2020)
Abstract
Whenever researchers write a paper, the same question occurs: ``Where to submit?'' In this work, we introduce WTS, an open and interpretable NLP system that recommends conferences and journals to researchers based on the title, abstract, and/or keywords of a given paper. We adapt the TextCNN architecture and automatically analyze its predictions using the Integrated Gradients method to highlight words and phrases that led to the recommendation of a scientific venue. We train and test our method on publications from the fields of artificial intelligence (AI) and medicine, both derived from the Semantic Scholar dataset. WTS achieves an Accuracy@5 of approximately 83\% for AI papers and 95\% in the field of medicine. It is open source and available for testing on https://wheretosubmit.ml.
%0 Conference Paper
%1 kobs2020where
%A Kobs, Konstantin
%A Koopmann, Tobias
%A Zehe, Albin
%A Fernes, David
%A Krop, Philipp
%A Hotho, Andreas
%B Findings of the Association for Computational Linguistics: EMNLP 2020
%C Online
%D 2020
%I Association for Computational Linguistics
%K 2020 bert myown nlp paper research venue
%P 878--883
%T Where to Submit? Helping Researchers to Choose the Right Venue
%U https://www.aclweb.org/anthology/2020.findings-emnlp.78
%X Whenever researchers write a paper, the same question occurs: ``Where to submit?'' In this work, we introduce WTS, an open and interpretable NLP system that recommends conferences and journals to researchers based on the title, abstract, and/or keywords of a given paper. We adapt the TextCNN architecture and automatically analyze its predictions using the Integrated Gradients method to highlight words and phrases that led to the recommendation of a scientific venue. We train and test our method on publications from the fields of artificial intelligence (AI) and medicine, both derived from the Semantic Scholar dataset. WTS achieves an Accuracy@5 of approximately 83\% for AI papers and 95\% in the field of medicine. It is open source and available for testing on https://wheretosubmit.ml.
@inproceedings{kobs2020where,
abstract = {Whenever researchers write a paper, the same question occurs: {``}Where to submit?{''} In this work, we introduce WTS, an open and interpretable NLP system that recommends conferences and journals to researchers based on the title, abstract, and/or keywords of a given paper. We adapt the TextCNN architecture and automatically analyze its predictions using the Integrated Gradients method to highlight words and phrases that led to the recommendation of a scientific venue. We train and test our method on publications from the fields of artificial intelligence (AI) and medicine, both derived from the Semantic Scholar dataset. WTS achieves an Accuracy@5 of approximately 83{\%} for AI papers and 95{\%} in the field of medicine. It is open source and available for testing on https://wheretosubmit.ml.},
added-at = {2020-11-19T16:27:24.000+0100},
address = {Online},
author = {Kobs, Konstantin and Koopmann, Tobias and Zehe, Albin and Fernes, David and Krop, Philipp and Hotho, Andreas},
biburl = {https://www.bibsonomy.org/bibtex/26fcdcb5345f4bb7b10fb479edb4fd608/hotho},
booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2020},
interhash = {934909835b777cb85ad566ef1a8dd3d5},
intrahash = {6fcdcb5345f4bb7b10fb479edb4fd608},
keywords = {2020 bert myown nlp paper research venue},
month = nov,
pages = {878--883},
publisher = {Association for Computational Linguistics},
timestamp = {2021-01-24T22:43:11.000+0100},
title = {Where to Submit? Helping Researchers to Choose the Right Venue},
url = {https://www.aclweb.org/anthology/2020.findings-emnlp.78},
year = 2020
}