@inproceedings{kobs-etal-2020-submit,
title = "Where to Submit? Helping Researchers to Choose the Right Venue",
author = "Kobs, Konstantin and
Koopmann, Tobias and
Zehe, Albin and
Fernes, David and
Krop, Philipp and
Hotho, Andreas",
editor = "Cohn, Trevor and
He, Yulan and
Liu, Yang",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.findings-emnlp.78",
doi = "10.18653/v1/2020.findings-emnlp.78",
pages = "878--883",
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 \url{https://wheretosubmit.ml}.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Where to Submit? Helping Researchers to Choose the Right Venue
%A Kobs, Konstantin
%A Koopmann, Tobias
%A Zehe, Albin
%A Fernes, David
%A Krop, Philipp
%A Hotho, Andreas
%Y Cohn, Trevor
%Y He, Yulan
%Y Liu, Yang
%S Findings of the Association for Computational Linguistics: EMNLP 2020
%D 2020
%8 November
%I Association for Computational Linguistics
%C Online
%F kobs-etal-2020-submit
%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.
%R 10.18653/v1/2020.findings-emnlp.78
%U https://aclanthology.org/2020.findings-emnlp.78
%U https://doi.org/10.18653/v1/2020.findings-emnlp.78
%P 878-883
Markdown (Informal)
[Where to Submit? Helping Researchers to Choose the Right Venue](https://aclanthology.org/2020.findings-emnlp.78) (Kobs et al., Findings 2020)
ACL