{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T10:16:46Z","timestamp":1776334606045,"version":"3.51.2"},"reference-count":54,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"8","license":[{"start":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T00:00:00Z","timestamp":1659312000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T00:00:00Z","timestamp":1659312000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T00:00:00Z","timestamp":1659312000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2022,8,1]]},"DOI":"10.1109\/tkde.2020.3030623","type":"journal-article","created":{"date-parts":[[2020,10,13]],"date-time":"2020-10-13T19:50:38Z","timestamp":1602618638000},"page":"3854-3866","source":"Crossref","is-referenced-by-count":19,"title":["Learning Latent Multi-Criteria Ratings From User Reviews for Recommendations"],"prefix":"10.1109","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4957-3064","authenticated-orcid":false,"given":"Pan","family":"Li","sequence":"first","affiliation":[{"name":"Department of Technology, Operation and Statistics, Stern School of Business, New York University, New York, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexander","family":"Tuzhilin","sequence":"additional","affiliation":[{"name":"Department of Technology, Operation and Statistics, Stern School of Business, New York University, New York, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2005.99"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4899-7637-6_1"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4899-7637-6_25"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1287\/isre.1100.0336"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/2229012.2229065"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/s40558-014-0010-z"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3298689.3347068"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098170"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3109859.3109905"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186145"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/1835804.1835903"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2012.110"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/2507157.2507163"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s11257-015-9155-5"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3158369"},{"key":"ref16","first-page":"854","article-title":"Learning k-way d-dimensional discrete codes for compact embedding representations","author":"Chen","year":"2018"},{"key":"ref17","article-title":"Compressing word embeddings via deep compositional code learning","author":"Shu","year":"2018"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3041823.3041824"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICWS.2019.00054"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.6077"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3018661.3018665"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783273"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098077"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186070"},{"key":"ref25","first-page":"2986","article-title":"Collaborative multi-level embedding learning from reviews for rating prediction","volume-title":"Proc. 25th Int. Joint Conf. Artif. Intell.","author":"Zhang"},{"key":"ref26","first-page":"3104","article-title":"Sequence to sequence learning with neural networks","volume-title":"Proc. Advances Neural Inf. Process. Syst.","author":"Sutskever"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/d14-1179"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.5555\/3044805.3045025"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/P15-1107"},{"key":"ref30","first-page":"1727","article-title":"Neural variational inference for text processing","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Miao"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/997817.997857"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijar.2008.11.006"},{"key":"ref33","first-page":"353","article-title":"Minimal loss hashing for compact binary codes","volume-title":"Proc. 28th Int. Conf. Mach. Learn.","author":"Norouzi"},{"key":"ref34","first-page":"1753","article-title":"Spectral hashing","volume-title":"Proc. Advances Neural Inf. Process. Syst.","author":"Weiss"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/3077136.3080842"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-1190"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1011"},{"key":"ref38","article-title":"Auto-encoding variational bayes","author":"Kingma","year":"2014"},{"key":"ref39","article-title":"Categorical reparameterization with gumbel-softmax","author":"Jang","year":"2017"},{"key":"ref40","article-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling","author":"Chung","year":"2014"},{"key":"ref41","article-title":"Statistical theory of extreme values and some practical applications","volume":"33","author":"Gumbel","year":"1954","journal-title":"NBS Appl. Math. Ser."},{"key":"ref42","first-page":"3086","article-title":"A* sampling","volume-title":"Proc. Advances Neural Inf. Process. Syst.","author":"Maddison"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-04898-2_455"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/963770.963772"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.21236\/ADA164453"},{"key":"ref47","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2015"},{"key":"ref48","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"Ioffe","year":"2015"},{"key":"ref49","first-page":"5767","article-title":"Improved training of wasserstein GANs","volume-title":"Proc. Advances Neural Inf. Process. Syst.","author":"Gulrajani"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-009-0295-6"},{"key":"ref51","first-page":"5675","article-title":"Gain: Missing data imputation using generative adversarial nets","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Yoon"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93040-4_21"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v045.i03"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btr597"}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/69\/9817411\/09222083.pdf?arnumber=9222083","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,9]],"date-time":"2024-01-09T23:34:46Z","timestamp":1704843286000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9222083\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,1]]},"references-count":54,"journal-issue":{"issue":"8"},"URL":"https:\/\/doi.org\/10.1109\/tkde.2020.3030623","relation":{},"ISSN":["1041-4347","1558-2191","2326-3865"],"issn-type":[{"value":"1041-4347","type":"print"},{"value":"1558-2191","type":"electronic"},{"value":"2326-3865","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,8,1]]}}}