{"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/domain-adaptation-of-thai-word-segmentation","title":"Domain Adaptation of Thai Word Segmentation Models using Stacked Ensemble","arxiv_id":null,"date":"2020-11-01","proceeding":"EMNLP 2020 11","authors":["Peerat Limkonchotiwat","Wannaphong Phatthiyaphaibun","Raheem Sarwar","Ekapol Chuangsuwanich","Sarana Nutanong"],"abstract":"Like many Natural Language Processing tasks, Thai word segmentation is domain-dependent. Researchers have been relying on transfer learning to adapt an existing model to a new domain. However, this approach is inapplicable to cases where we can interact with only input and output layers of the models, also known as {``}black boxes{''}. We propose a filter-and-refine solution based on the stacked-ensemble learning paradigm to address this black-box limitation. We conducted extensive experimental studies comparing our method against state-of-the-art models and transfer learning. Experimental results show that our proposed solution is an effective domain adaptation method and has a similar performance as the transfer learning method.","url_abs":"https://aclanthology.org/2020.emnlp-main.315","url_pdf":"https://aclanthology.org/2020.emnlp-main.315.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":"domain-adaptation-of-thai-word-segmentation","repo_url":"https://github.com/mrpeerat/SEFR_CUT","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"domain-adaptation","task_name":"Domain Adaptation"},{"task_slug":"ensemble-learning","task_name":"Ensemble Learning"},{"task_slug":"thai-word-segmentation","task_name":"Thai Word Segmentation"},{"task_slug":"transfer-learning","task_name":"Transfer Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/thai-word-tokenization-on-best-2010","task":"Thai Word Segmentation","dataset":"BEST-2010","model":"Stacked Ensemble (CRF)","rank_in_archive_order":5,"of":5,"metrics":{"F1-Score":"0.9812"},"uses_additional_data":false},{"leaderboard":"/sota/thai-word-segmentation-on-ws160","task":"Thai Word Segmentation","dataset":"WS160","model":"Stacked Ensemble (CRF)","rank_in_archive_order":1,"of":1,"metrics":{"F1-score":"0.952"},"uses_additional_data":true}],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}