{"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/neural-word-segmentation-learning-for-chinese","title":"Neural Word Segmentation Learning for Chinese","arxiv_id":"1606.04300","date":"2016-06-14","proceeding":"ACL 2016 8","authors":["Deng Cai","Hai Zhao"],"abstract":"Most previous approaches to Chinese word segmentation formalize this problem\nas a character-based sequence labeling task where only contextual information\nwithin fixed sized local windows and simple interactions between adjacent tags\ncan be captured. In this paper, we propose a novel neural framework which\nthoroughly eliminates context windows and can utilize complete segmentation\nhistory. Our model employs a gated combination neural network over characters\nto produce distributed representations of word candidates, which are then given\nto a long short-term memory (LSTM) language scoring model. Experiments on the\nbenchmark datasets show that without the help of feature engineering as most\nexisting approaches, our models achieve competitive or better performances with\nprevious state-of-the-art methods.","url_abs":"http://arxiv.org/abs/1606.04300v2","url_pdf":"http://arxiv.org/pdf/1606.04300v2.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":"neural-word-segmentation-learning-for-chinese","repo_url":"https://github.com/jcyk/CWS","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"chinese-word-segmentation","task_name":"Chinese Word Segmentation"},{"task_slug":"feature-engineering","task_name":"Feature Engineering"},{"task_slug":"segmentation","task_name":"Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1606.04300","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}