{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,18]],"date-time":"2024-10-18T04:28:31Z","timestamp":1729225711149,"version":"3.27.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643685489","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,10,16]],"date-time":"2024-10-16T00:00:00Z","timestamp":1729036800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,10,16]]},"abstract":"<jats:p>We propose a Skew-Symmetric Bilinear (SSB) model to represent intransitive preferences on subsets of a ground set of items. More precisely, the SSB model accounts for preference intensities between pairs of subsets. We provide a procedure to learn the parameters of the SSB model from a set of known pairwise preferences between subsets, managing to find a sparse model, and as simple as possible in terms of the degree of interaction between items. The SSB model can be viewed as a concise representation of a weighted tournament on subsets. We study the complexity of determining the winners according to various tournament rules. Numerical tests on synthetic and real-world data are carried out.<\/jats:p>","DOI":"10.3233\/faia240887","type":"book-chapter","created":{"date-parts":[[2024,10,17]],"date-time":"2024-10-17T13:38:05Z","timestamp":1729172285000},"source":"Crossref","is-referenced-by-count":0,"title":["Learning and Optimizing with an SSB Representation of Intransitive Preferences on Sets"],"prefix":"10.3233","author":[{"given":"Hugo","family":"Gilbert","sequence":"first","affiliation":[{"name":"Universit\u00e9 Paris-Dauphine, PSL University, CNRS, LAMSADE, Paris, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamed","family":"Ouaguenouni","sequence":"additional","affiliation":[{"name":"Sorbonne Universit\u00e9, CNRS, LIP6, Paris, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Olivier","family":"Spanjaard","sequence":"additional","affiliation":[{"name":"Sorbonne Universit\u00e9, CNRS, LIP6, Paris, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","ECAI 2024"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA240887","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,17]],"date-time":"2024-10-17T13:38:05Z","timestamp":1729172285000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA240887"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,16]]},"ISBN":["9781643685489"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia240887","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,16]]}}}