{"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-representative-keywords-selection-a","title":"Domain Representative Keywords Selection: A Probabilistic Approach","arxiv_id":"2203.10365","date":"2022-03-19","proceeding":"Findings (ACL) 2022 5","authors":["Pritom Saha Akash","Jie Huang","Kevin Chen-Chuan Chang","Yunyao Li","Lucian Popa","ChengXiang Zhai"],"abstract":"We propose a probabilistic approach to select a subset of a \\textit{target domain representative keywords} from a candidate set, contrasting with a context domain. Such a task is crucial for many downstream tasks in natural language processing. To contrast the target domain and the context domain, we adapt the \\textit{two-component mixture model} concept to generate a distribution of candidate keywords. It provides more importance to the \\textit{distinctive} keywords of the target domain than common keywords contrasting with the context domain. To support the \\textit{representativeness} of the selected keywords towards the target domain, we introduce an \\textit{optimization algorithm} for selecting the subset from the generated candidate distribution. We have shown that the optimization algorithm can be efficiently implemented with a near-optimal approximation guarantee. Finally, extensive experiments on multiple domains demonstrate the superiority of our approach over other baselines for the tasks of keyword summary generation and trending keywords selection.","url_abs":"https://arxiv.org/abs/2203.10365v2","url_pdf":"https://arxiv.org/pdf/2203.10365v2.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-representative-keywords-selection-a","repo_url":"https://github.com/pritomsaha/keyword-selection","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2203.10365","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}