{"type":"ScholarlyArticle","title":"An Empirical Investigation of Ceteris Paribus Learnability","authors":[{"name":"Loizos Michael","slug":"loizos-michael","given":"Loizos","family":"Michael","affiliation":""},{"name":"Elena Papageorgiou","slug":"elena-papageorgiou","given":"Elena","family":"Papageorgiou","affiliation":""}],"abstract":"Eliciting user preferences constitutes a major step towards developing recommender systems and decision support tools. Assuming that preferences are ceteris paribus allows for their concise representation as Conditional Preference Networks (CP-nets). This work presents the first empirical investigation of an algorithm for reliably and efficiently learning CP-nets in a manner that is minimally intrusive. At the same time, it introduces a novel process for efficiently reasoning with (the learned) preferences.","doi":null,"url":"https://ijcai.org/proceedings/2013/229","pdf":"https://ijcai.org/proceedings/2013/0229.pdf","markdown":"https://ijcai.org/proceedings/2013/229.md","bibtex":"https://ijcai.org/proceedings/2013/bibtex/229","volume":{"slug":"2013","title":"Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2013","url":"https://ijcai.org/proceedings/2013/","year":2013,"location":"Beijing, China","dates":"3–9 August 2013","editors":"Francesca Rossi","isbn":"978-1-57735-633-2","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":229,"pages":{"first":1537,"last":1542},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}