{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/where-to-submit-helping-researchers-to-choose","title":"Where to Submit? Helping Researchers to Choose the Right Venue","arxiv_id":null,"date":"2020-11-01","proceeding":"Findings of the Association for Computational Linguistics 2020","authors":["Konstantin Kobs","Tobias Koopmann","Albin Zehe","David Fernes","Philipp Krop","Andreas Hotho"],"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.","url_abs":"https://aclanthology.org/2020.findings-emnlp.78","url_pdf":"https://aclanthology.org/2020.findings-emnlp.78.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"where-to-submit-helping-researchers-to-choose","repo_url":"https://github.com/konstantinkobs/wts","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}