{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T07:52:47Z","timestamp":1772265167392,"version":"3.50.1"},"posted":{"date-parts":[[2018,11,27]]},"group-title":"PeerJ Preprints","reference-count":0,"publisher":"PeerJ","license":[{"start":{"date-parts":[[2018,11,27]],"date-time":"2018-11-27T00:00:00Z","timestamp":1543276800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>Playlist recommendation involves producing a set of songs that a user might enjoy. We investigate this problem in three cold-start scenarios: (i) cold playlists, where we recommend songs to form new personalised playlists for an existing user; (ii) cold users, where we recommend songs to form new playlists for a new user; and (iii) cold songs, where we recommend newly released songs to extend users\u2019 existing playlists. We propose a flexible multitask learning method to deal with all three settings. The method learns from user-curated playlists, and encourages songs in a playlist to be ranked higher than those that are not by minimising a bipartite ranking loss. Inspired by an equivalence between bipartite ranking and binary classification, we show how one can efficiently approximate an optimal solution of the multitask learning objective by minimising a classification loss. Empirical results on two real playlist datasets show the proposed approach has good performance for cold-start playlist recommendation.<\/jats:p>","DOI":"10.7287\/peerj.preprints.27383v2","type":"posted-content","created":{"date-parts":[[2018,11,27]],"date-time":"2018-11-27T10:13:26Z","timestamp":1543313606000},"source":"Crossref","is-referenced-by-count":0,"title":["Cold-start playlist recommendation with multitask learning"],"prefix":"10.7287","author":[{"given":"Dawei","family":"Chen","sequence":"first","affiliation":[{"name":"Research School of Computer Science, Australian National University, Canberra, ACT, Australia"},{"name":"Machine Learning Research Group, Data61, CSIRO, Canberra, ACT, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2302-9733","authenticated-orcid":true,"given":"Cheng Soon","family":"Ong","sequence":"additional","affiliation":[{"name":"Research School of Computer Science, Australian National University, Canberra, ACT, Australia"},{"name":"Machine Learning Research Group, Data61, CSIRO, Canberra, ACT, Australia"}]},{"given":"Aditya Krishna","family":"Menon","sequence":"additional","affiliation":[{"name":"Research School of Computer Science, Australian National University, Canberra, ACT, Australia"}]}],"member":"4443","container-title":[],"original-title":[],"link":[{"URL":"https:\/\/peerj.com\/preprints\/27383v2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/peerj.com\/preprints\/27383v2.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/peerj.com\/preprints\/27383v2.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/peerj.com\/preprints\/27383v2.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,12,23]],"date-time":"2019-12-23T20:04:54Z","timestamp":1577131494000},"score":1,"resource":{"primary":{"URL":"https:\/\/peerj.com\/preprints\/27383v2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,11,27]]},"references-count":0,"aliases":["10.7287\/peerj.preprints.27383"],"URL":"https:\/\/doi.org\/10.7287\/peerj.preprints.27383v2","relation":{"references":[{"id-type":"doi","id":"10.7287\/peerj.preprints.27383v2\/supp-1","asserted-by":"subject"},{"id-type":"doi","id":"10.7287\/peerj.preprints.27383v2\/supp-1","asserted-by":"object"}],"replaces":[{"id-type":"doi","id":"10.7287\/peerj.preprints.27383v1","asserted-by":"object"}]},"subject":[],"published":{"date-parts":[[2018,11,27]]},"subtype":"preprint"}}