{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T07:26:14Z","timestamp":1773213974328,"version":"3.50.1"},"reference-count":49,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61472340"],"award-info":[{"award-number":["61472340"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Hebei Provincial Department of Science and Technology","award":["20310301D"],"award-info":[{"award-number":["20310301D"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/access.2020.3007675","type":"journal-article","created":{"date-parts":[[2020,7,9]],"date-time":"2020-07-09T20:20:21Z","timestamp":1594326021000},"page":"131286-131298","source":"Crossref","is-referenced-by-count":12,"title":["Facing Cold-Start: A Live TV Recommender System Based on Neural Networks"],"prefix":"10.1109","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2790-3210","authenticated-orcid":false,"given":"Xiaosong","family":"Zhu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4907-0256","authenticated-orcid":false,"given":"Jingfeng","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4512-0431","authenticated-orcid":false,"given":"Shuang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3526-9109","authenticated-orcid":false,"given":"Tong","family":"Hao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219855"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219869"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2019.113045"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/3347449.3357487"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-020-08774-0"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2015.06.052"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2869470"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2014.05.003"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2019.2944214"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-018-6323-8"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TCE.2008.4637593"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.3390\/app8081323"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1142\/9789813275355_0014"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2005.99"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-72559-6_18"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2013.09.018"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2013.09.136"},{"key":"ref24","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"J Mach Learn Res"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3083187.3083194"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TAAI.2013.46"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3304112.3325606"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2016.01.018"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-39817-4_18"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219885"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2017.06.046"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2019.00036"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.22"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2017.04.038"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-85820-3_9"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3347449.3357485"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/1809777.1809832"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1051\/matecconf\/201816901003"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-85820-3_1"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/1014052.1014097"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1177\/1461444814538646"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/2959100.2959190"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-72079-9"},{"key":"ref7","first-page":"7","article-title":"Time-based TV programs prediction","author":"turrin","year":"2014","journal-title":"Proc 1st Workshop Rec Syst TV Online Video ACM (RecSys)"},{"key":"ref49","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","author":"glorot","year":"2010","journal-title":"Proc Int Conf Artif Intell Statist"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-27729-5_5"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/3285029"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/3084289.3089916"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2890293"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1145\/3079628.3079670"},{"key":"ref42","first-page":"452","article-title":"BPR: Bayesian personalized ranking from implicit feedback","author":"rendle","year":"2009","journal-title":"Proc Conf Uncertainty of Artificial Intelligence"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/3125486.3125492"},{"key":"ref44","article-title":"Entity embeddings of categorical variables","author":"guo","year":"2016","journal-title":"arXiv 1604 06737"},{"key":"ref43","author":"wyk","year":"0","journal-title":"Encoding Cyclical Features for Deep Learning"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8948470\/09137323.pdf?arnumber=9137323","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T15:57:22Z","timestamp":1642003042000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9137323\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":49,"URL":"https:\/\/doi.org\/10.1109\/access.2020.3007675","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]}}}