{"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/incremental-skip-gram-model-with-negative","title":"Incremental Skip-gram Model with Negative Sampling","arxiv_id":"1704.03956","date":"2017-04-13","proceeding":"EMNLP 2017 9","authors":["Nobuhiro Kaji","Hayato Kobayashi"],"abstract":"This paper explores an incremental training strategy for the skip-gram model\nwith negative sampling (SGNS) from both empirical and theoretical perspectives.\nExisting methods of neural word embeddings, including SGNS, are multi-pass\nalgorithms and thus cannot perform incremental model update. To address this\nproblem, we present a simple incremental extension of SGNS and provide a\nthorough theoretical analysis to demonstrate its validity. Empirical\nexperiments demonstrated the correctness of the theoretical analysis as well as\nthe practical usefulness of the incremental algorithm.","url_abs":"http://arxiv.org/abs/1704.03956v2","url_pdf":"http://arxiv.org/pdf/1704.03956v2.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":"incremental-skip-gram-model-with-negative","repo_url":"https://github.com/yahoojapan/yskip","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"word-embeddings","task_name":"Word Embeddings"},{"task_slug":"model","task_name":"model"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}