{"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/rank-pruning-for-dominance-queries-in-cp-nets","title":"Rank Pruning for Dominance Queries in CP-Nets","arxiv_id":"1712.08588","date":"2017-12-22","proceeding":null,"authors":["Kathryn Laing","Peter Adam Thwaites","John Paul Gosling"],"abstract":"Conditional preference networks (CP-nets) are a graphical representation of a\nperson's (conditional) preferences over a set of discrete variables. In this\npaper, we introduce a novel method of quantifying preference for any given\noutcome based on a CP-net representation of a user's preferences. We\ndemonstrate that these values are useful for reasoning about user preferences.\nIn particular, they allow us to order (any subset of) the possible outcomes in\naccordance with the user's preferences. Further, these values can be used to\nimprove the efficiency of outcome dominance testing. That is, given a pair of\noutcomes, we can determine which the user prefers more efficiently. Through\nexperimental results, we show that this method is more effective than existing\ntechniques for improving dominance testing efficiency. We show that the above\nresults also hold for CP-nets that express indifference between variable\nvalues.","url_abs":"http://arxiv.org/abs/1712.08588v2","url_pdf":"http://arxiv.org/pdf/1712.08588v2.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":"rank-pruning-for-dominance-queries-in-cp-nets","repo_url":"https://github.com/KathrynLaing/DQ-Pruning","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":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}