{"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/finding-average-regret-ratio-minimizing-set","title":"Finding Average Regret Ratio Minimizing Set in Database","arxiv_id":"1810.08047","date":"2018-10-18","proceeding":null,"authors":["Sepanta Zeighami","Raymong Chi-Wing Wong"],"abstract":"Selecting a certain number of data points (or records) from a database which\n\"best\" satisfy users' expectations is a very prevalent problem with many\napplications. One application is a hotel booking website showing a certain\nnumber of hotels on a single page. However, this problem is very challenging\nsince the selected points should \"collectively\" satisfy the expectation of all\nusers. Showing a certain number of data points to a single user could decrease\nthe satisfaction of a user because the user may not be able to see his/her\nfavorite point which could be found in the original database. In this paper, we\nwould like to find a set of k points such that on average, the satisfaction\n(ratio) of a user is maximized. This problem takes into account the probability\ndistribution of the users and considers the satisfaction (ratio) of all users,\nwhich is more reasonable in practice, compared with the existing studies that\nonly consider the worst-case satisfaction (ratio) of the users, which may not\nreflect the whole population and is not useful in some applications. Motivated\nby this, in this paper, we propose algorithms for this problem. Finally, we\nconducted experiments to show the effectiveness and the efficiency of the\nalgorithms.","url_abs":"http://arxiv.org/abs/1810.08047v1","url_pdf":"http://arxiv.org/pdf/1810.08047v1.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":"finding-average-regret-ratio-minimizing-set","repo_url":"https://github.com/szeighami/FAM_Continuous-DP","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"finding-average-regret-ratio-minimizing-set","repo_url":"https://github.com/szeighami/FAM_Discrete-DP","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"finding-average-regret-ratio-minimizing-set","repo_url":"https://github.com/szeighami/FAM_Greedy-Shrink","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}