{"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/snu_ids-at-semeval-2019-task-3-addressing","title":"SNU_IDS at SemEval-2019 Task 3: Addressing Training-Test Class Distribution Mismatch in Conversational Classification","arxiv_id":"1903.02163","date":"2019-03-06","proceeding":null,"authors":["Sanghwan Bae","Jihun Choi","Sang-goo Lee"],"abstract":"We present several techniques to tackle the mismatch in class distributions\nbetween training and test data in the Contextual Emotion Detection task of\nSemEval 2019, by extending the existing methods for class imbalance problem.\nReducing the distance between the distribution of prediction and ground truth,\nthey consistently show positive effects on the performance. Also we propose a\nnovel neural architecture which utilizes representation of overall context as\nwell as of each utterance. The combination of the methods and the models\nachieved micro F1 score of about 0.766 on the final evaluation.","url_abs":"http://arxiv.org/abs/1903.02163v2","url_pdf":"http://arxiv.org/pdf/1903.02163v2.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":"snu_ids-at-semeval-2019-task-3-addressing","repo_url":"https://github.com/baaesh/semeval19_task3","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"classification","task_name":"General Classification"}],"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}