{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T00:16:43Z","timestamp":1758845803911,"version":"3.37.3"},"reference-count":51,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,6,1]],"date-time":"2021-06-01T00:00:00Z","timestamp":1622505600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61932007","U1630115"],"award-info":[{"award-number":["61932007","U1630115"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2021,6,1]]},"DOI":"10.1109\/tkde.2019.2955100","type":"journal-article","created":{"date-parts":[[2019,11,22]],"date-time":"2019-11-22T21:17:33Z","timestamp":1574457453000},"page":"2640-2653","source":"Crossref","is-referenced-by-count":10,"title":["Mixture Matrix Approximation for Collaborative Filtering"],"prefix":"10.1109","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3103-8442","authenticated-orcid":false,"given":"Dongsheng","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3911-8711","authenticated-orcid":false,"given":"Chao","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tun","family":"Lu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stephen M.","family":"Chu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ning","family":"Gu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","first-page":"452","article-title":"BPR: Bayesian personalized ranking from implicit feedback","author":"rendle","year":"2009","journal-title":"Proc 25th Conf Uncertainty Artif Intell"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/2556195.2556248"},{"key":"ref33","first-page":"1134","article-title":"Divide-and-conquer matrix factorization","author":"mackey","year":"2011","journal-title":"Proc 24th Int Conf Neural Inf Process Syst"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/MIC.2003.1167344"},{"key":"ref31","first-page":"897","article-title":"McRank: Learning to rank using multiple classification and gradient boosting","author":"li","year":"2008","journal-title":"Proc 20th Int Conf Neural Inf Process Syst"},{"key":"ref30","first-page":"295","article-title":"Low-rank matrix approximation with stability","author":"li","year":"2016","journal-title":"Proc 33rd Int Conf Mach Learn"},{"key":"ref37","first-page":"1","article-title":"JSAT: Java statistical analysis tool, a library for machine learning","volume":"18","author":"raff","year":"2017","journal-title":"J Mach Learn Res"},{"key":"ref36","first-page":"5","article-title":"Improving regularized singular value decomposition for collaborative filtering","author":"paterek","year":"2007","journal-title":"Proc KDD Cup"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.16"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2011.134"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186155"},{"key":"ref27","first-page":"477","article-title":"Mixture-Rank matrix approximation for collaborative filtering","author":"li","year":"2017","journal-title":"Proc Neural Inf Process Syst 30"},{"key":"ref29","first-page":"1403","article-title":"ERMMA: Expected risk minimization for matrix approximation-based recommender systems","author":"li","year":"2017","journal-title":"Proc 31st AAAI Conf Artif Intell"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-02247-0_24"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2005.99"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/2487575.2487589"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1401944"},{"article-title":"Adam: A method for stochastic optimization","year":"2014","author":"kingma","key":"ref21"},{"key":"ref24","first-page":"231","article-title":"Neural network ensembles, cross validation and active learning","author":"krogh","year":"1994","journal-title":"Proc 7th Int Conf Neural Inf Process Syst"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"ref26","first-page":"82","article-title":"Local low-rank matrix approximation","author":"lee","year":"2013","journal-title":"Proc 30th Int Conf Mach Learn"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/2566486.2567970"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1145\/2488388.2488520"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1201\/b12207"},{"key":"ref10","first-page":"1382","article-title":"MPMA: Mixture probabilistic matrix approximation for collaborative filtering","author":"chen","year":"2016","journal-title":"Proc 25th Int Joint Conf Artif Intell"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/2766462.2767718"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/1454008.1454047"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2013.6639346"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/1242572.1242610"},{"key":"ref14","first-page":"2004","article-title":"Probabilistic sparse matrix factorization","author":"dueck","year":"2004"},{"key":"ref15","first-page":"315","article-title":"Deep sparse rectifier neural networks","author":"glorot","year":"2011","journal-title":"Proc 14th Int Conf Artif Intell Statist"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052569"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/2911451.2911489"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1214\/009053607000000677"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.22"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052713"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/2736277.2741091"},{"key":"ref6","first-page":"46","article-title":"Learning collaborative information filters","author":"billsus","year":"1998","journal-title":"Proc 15th Int Conf Mach Learn"},{"key":"ref5","first-page":"2131","article-title":"Probabilistic low-rank matrix completion from quantized measurements","volume":"17","author":"bhaskar","year":"2016","journal-title":"J Mach Learn Res"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/BF00048682"},{"key":"ref49","first-page":"222","article-title":"Recommendation by mining multiple user behaviors with group sparsity","author":"yuan","year":"2014","journal-title":"Proc 28th AAAI Conf Artif Intell"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CAMSAP.2015.7383813"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2013.157"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-41357-0"},{"key":"ref48","first-page":"1593","article-title":"COFiRANK maximum margin matrix factorization for collaborative ranking","author":"weimer","year":"2007","journal-title":"Proc 20th Int Conf Neural Inf Process Syst"},{"key":"ref47","article-title":"How diverse is your audience? exploring consumer diversity in recommender systems","author":"wasilewski","year":"2017","journal-title":"Proc 11th ACM Conf Recommender Syst"},{"key":"ref42","first-page":"1257","article-title":"Probabilistic matrix factorization","author":"salakhutdinov","year":"2008","journal-title":"Proc 20th Int Conf Neural Inf Process Syst"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390267"},{"key":"ref44","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":"ref43","doi-asserted-by":"publisher","DOI":"10.21236\/ADA439541"}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/69\/9427778\/08910350.pdf?arnumber=8910350","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:50:53Z","timestamp":1652194253000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8910350\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,1]]},"references-count":51,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tkde.2019.2955100","relation":{},"ISSN":["1041-4347","1558-2191","2326-3865"],"issn-type":[{"type":"print","value":"1041-4347"},{"type":"electronic","value":"1558-2191"},{"type":"electronic","value":"2326-3865"}],"subject":[],"published":{"date-parts":[[2021,6,1]]}}}