| dc.contributor.author | Skowron, Piotr | |
| dc.contributor.author | Faliszewski, Piotr | |
| dc.contributor.author | Lang, Jérôme | |
| dc.date.accessioned | 2017-01-18T13:09:22Z | |
| dc.date.available | 2017-01-18T13:09:22Z | |
| dc.date.issued | 2016 | |
| dc.identifier.issn | 0004-3702 | |
| dc.identifier.uri | https://basepub.dauphine.fr/handle/123456789/16189 | |
| dc.language.iso | en | en |
| dc.subject | Proportional representation | en |
| dc.subject | Ordered weighted average | en |
| dc.subject | Chamberlin–Courant rule | en |
| dc.subject | Computational complexity | en |
| dc.subject | Computational social choice | en |
| dc.subject | Approximation | en |
| dc.subject | Elections | en |
| dc.subject | Voting | en |
| dc.subject.ddc | 006.3 | en |
| dc.title | Finding a collective set of items: From proportional multirepresentation to group recommendation | en |
| dc.type | Article accepté pour publication ou publié | |
| dc.description.abstracten | We consider the following problem: There is a set of items (e.g., movies) and a group of agents (e.g., passengers on a plane); each agent has some intrinsic utility for each of the items. Our goal is to pick a set of K items that maximize the total derived utility of all the agents (i.e., in our example we are to pick K movies that we put on the plane's entertainment system). However, the actual utility that an agent derives from a given item is only a fraction of its intrinsic one, and this fraction depends on how the agent ranks the item among the chosen, available, ones. We provide a formal specification of the model and provide concrete examples and settings where it is applicable. We show that the problem is hard in general, but we show a number of tractability results for its natural special cases. | en |
| dc.relation.isversionofjnlname | Artificial Intelligence | |
| dc.relation.isversionofjnlissue | 241 | en |
| dc.relation.isversionofjnldate | 2016-12 | |
| dc.relation.isversionofjnlpages | 191-216 | en |
| dc.relation.isversionofdoi | 10.1016/j.artint.2016.09.003 | en |
| dc.relation.isversionofjnlpublisher | Elsevier | en |
| dc.subject.ddclabel | Intelligence artificielle | en |
| dc.relation.forthcoming | non | en |
| dc.relation.forthcomingprint | non | en |
| dc.description.ssrncandidate | non | en |
| dc.description.halcandidate | oui | en |
| dc.description.readership | recherche | en |
| dc.description.audience | International | en |
| dc.relation.Isversionofjnlpeerreviewed | oui | en |
| dc.relation.Isversionofjnlpeerreviewed | oui | en |
| dc.date.updated | 2017-01-18T13:00:09Z | |
| hal.person.labIds | 98120 | |
| hal.person.labIds | 200767 | |
| hal.person.labIds | 989 | |
| hal.identifier | hal-01439247 | * |
