{"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/improving-sparse-word-representations-with","title":"Improving Sparse Word Representations with Distributional Inference for Semantic Composition","arxiv_id":"1608.06794","date":"2016-08-24","proceeding":"EMNLP 2016 11","authors":["Thomas Kober","Julie Weeds","Jeremy Reffin","David Weir"],"abstract":"Distributional models are derived from co-occurrences in a corpus, where only\na small proportion of all possible plausible co-occurrences will be observed.\nThis results in a very sparse vector space, requiring a mechanism for inferring\nmissing knowledge. Most methods face this challenge in ways that render the\nresulting word representations uninterpretable, with the consequence that\nsemantic composition becomes hard to model. In this paper we explore an\nalternative which involves explicitly inferring unobserved co-occurrences using\nthe distributional neighbourhood. We show that distributional inference\nimproves sparse word representations on several word similarity benchmarks and\ndemonstrate that our model is competitive with the state-of-the-art for\nadjective-noun, noun-noun and verb-object compositions while being fully\ninterpretable.","url_abs":"http://arxiv.org/abs/1608.06794v1","url_pdf":"http://arxiv.org/pdf/1608.06794v1.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":"improving-sparse-word-representations-with","repo_url":"https://github.com/tttthomasssss/apt-toolkit","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"semantic-composition","task_name":"Semantic Composition"},{"task_slug":"word-similarity","task_name":"Word Similarity"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}