{"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/zoho-at-semeval-2019-task-9-semi-supervised","title":"Zoho at SemEval-2019 Task 9: Semi-supervised Domain Adaptation using Tri-training for Suggestion Mining","arxiv_id":"1902.10623","date":"2019-02-27","proceeding":"SEMEVAL 2019 6","authors":["Sai Prasanna","Sri Ananda Seelan"],"abstract":"This paper describes our submission for the SemEval-2019 Suggestion Mining\ntask. A simple Convolutional Neural Network (CNN) classifier with contextual\nword representations from a pre-trained language model was used for sentence\nclassification. The model is trained using tri-training, a semi-supervised\nbootstrapping mechanism for labelling unseen data. Tri-training proved to be an\neffective technique to accommodate domain shift for cross-domain suggestion\nmining (Subtask B) where there is no hand labelled training data. For in-domain\nevaluation (Subtask A), we use the same technique to augment the training set.\nOur system ranks thirteenth in Subtask A with an $F_1$-score of 68.07 and third\nin Subtask B with an $F_1$-score of 81.94.","url_abs":"http://arxiv.org/abs/1902.10623v2","url_pdf":"http://arxiv.org/pdf/1902.10623v2.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":"zoho-at-semeval-2019-task-9-semi-supervised","repo_url":"https://github.com/sai-prasanna/suggestion-mining-semeval19","is_official":0,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"domain-adaptation","task_name":"Domain Adaptation"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"language-modeling","task_name":"Language Modeling"},{"task_slug":"language-modelling","task_name":"Language Modelling"},{"task_slug":"semi-supervised-domain-adaptation","task_name":"Semi-supervised Domain Adaptation"},{"task_slug":"sentence","task_name":"Sentence"},{"task_slug":"sentence-classification","task_name":"Sentence Classification"},{"task_slug":"suggestion-mining","task_name":"Suggestion mining"}],"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}