{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T23:06:35Z","timestamp":1768777595913,"version":"3.49.0"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,8]]},"abstract":"<jats:p>A public divisible resource is to be divided among projects. We study rules that decide on a distribution of the budget when voters have ordinal preference rankings over projects. Examples of such portioning problems are participatory budgeting, time shares, and parliament elections. We introduce a family of rules for portioning, inspired by positional scoring rules. Rules in this family are given by a scoring vector (such as plurality or Borda) associating a positive value with each rank in a vote, and an aggregation function such as leximin or the Nash product. Our family contains well-studied rules, but most are new. We discuss computational and normative properties of our rules. We focus on fairness, and introduce the SD-core, a group fairness notion. Our Nash rules are in the SD-core, and the leximin rules satisfy individual fairness properties. Both are Pareto-efficient.<\/jats:p>","DOI":"10.24963\/ijcai.2019\/2","type":"proceedings-article","created":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T07:46:05Z","timestamp":1564299965000},"page":"11-17","source":"Crossref","is-referenced-by-count":4,"title":["Portioning Using Ordinal Preferences: Fairness and Efficiency"],"prefix":"10.24963","author":[{"given":"St\u00e9phane","family":"Airiau","sequence":"first","affiliation":[{"name":"LAMSADE, CNRS, Universit\u00e9 Paris-Dauphine, PSL University"}]},{"given":"Haris","family":"Aziz","sequence":"additional","affiliation":[{"name":"UNSW Sydney & Data61, CSIRO"}]},{"given":"Ioannis","family":"Caragiannis","sequence":"additional","affiliation":[{"name":"University of Patras"}]},{"given":"Justin","family":"Kruger","sequence":"additional","affiliation":[{"name":"LAMSADE, CNRS, Universit\u00e9 Paris-Dauphine, PSL University"}]},{"given":"J\u00e9r\u00f4me","family":"Lang","sequence":"additional","affiliation":[{"name":"LAMSADE, CNRS, Universit\u00e9 Paris-Dauphine, PSL University"}]},{"given":"Dominik","family":"Peters","sequence":"additional","affiliation":[{"name":"University of Oxford"}]}],"member":"10584","event":{"name":"Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}","theme":"Artificial Intelligence","location":"Macao, China","acronym":"IJCAI-2019","number":"28","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2019,8,10]]},"end":{"date-parts":[[2019,8,16]]}},"container-title":["Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T07:46:09Z","timestamp":1564299969000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2019\/2"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2019,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2019\/2","relation":{},"subject":[],"published":{"date-parts":[[2019,8]]}}}