{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T13:10:18Z","timestamp":1775913018540,"version":"3.50.1"},"reference-count":54,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"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":["62036005"],"award-info":[{"award-number":["62036005"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61771348"],"award-info":[{"award-number":["61771348"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["2042020KF0205"],"award-info":[{"award-number":["2042020KF0205"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Multimedia"],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/tmm.2021.3111487","type":"journal-article","created":{"date-parts":[[2021,9,10]],"date-time":"2021-09-10T20:14:37Z","timestamp":1631304877000},"page":"1067-1079","source":"Crossref","is-referenced-by-count":52,"title":["Multi-Modal Variational Graph Auto-Encoder for Recommendation Systems"],"prefix":"10.1109","volume":"24","author":[{"given":"Jing","family":"Yi","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7882-1066","authenticated-orcid":false,"given":"Zhenzhong","family":"Chen","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/MIC.2017.72"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3326937.3341261"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/1719970.1719976"},{"key":"ref4","article-title":"A system for online news recommendations in real-time with apache mahout","volume-title":"Proc. Conf. Labs Eval. Forum","author":"Beck","year":"2017"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/2959100.2959190"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3240323.3241730"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411947"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/1961209.1961213"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3351034"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/1148170.1148257"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/371920.372071"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.5555\/2981562.2981720"},{"issue":"1","key":"ref14","first-page":"3367","article-title":"Matrix completion and low-rank SVD via fast alternating least squares","volume":"16","author":"Hastie","year":"2015","journal-title":"J. Mach. Learn. Res."},{"key":"ref15","first-page":"8","article-title":"Incremental singular value decomposition algorithms for highly scalable recommender systems","volume-title":"Proc. Int. Conf. Comput. Inf. Sci.","author":"Sarwar","year":"2002"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v30i1.9973"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3125486.3125492"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132892"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3350953"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.18178\/wcse.2019.06.016"},{"key":"ref21","article-title":"Auto-encoding variational bayes","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Kingma","year":"2014"},{"key":"ref22","first-page":"5575","article-title":"Multimodal generative models for scalable weakly-supervised learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Wu","year":"2018"},{"key":"ref23","article-title":"Session-based recommendations with recurrent neural networks","volume-title":"Int. Conf. Learn. Representations","author":"Hidasi","year":"2016"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-19274-7_47"},{"key":"ref25","first-page":"18","article-title":"On the importance of news content representation in hybrid neural session-based recommender systems","volume-title":"Proc. Int. Workshop News Recommendation Analytics","author":"Moreira","year":"2019"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1002\/sam.11184"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/2484028.2484194"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3206025.3210497"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2881260"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2019.2940709"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2021.3073267"},{"key":"ref32","article-title":"Graph convolutional matrix completion","volume-title":"Proc. ACM SIGKDD Int. Conf. Knowl. Discov. Data Mining Workshop Deep Learn. Day","author":"den","year":"2018"},{"key":"ref33","article-title":"Variational graph auto-encoders","volume-title":"Proc. Adv. Neural Inf. Process. Syst. Workshop Bayesian Deep Learn.","author":"Kipf","year":"2016"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331267"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401063"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403388"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219869"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623732"},{"key":"ref39","article-title":"Efficient estimation of word representations in vector space","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Mikolov","year":"2013"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219890"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403284"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186150"},{"key":"ref43","first-page":"5712","article-title":"Learning disentangled representations for recommendation","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Ma","year":"2019"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098077"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref46","article-title":"Rectifier nonlinearities improve neural network acoustic models","volume-title":"ICML Workshop Deep Learn. Audio, Speech Lang. Process.","author":"Maas"},{"key":"ref47","article-title":"Joint multimodal learning with deep generative models","volume-title":"Proc. Int. Conf. Learn. Representations Workshops","author":"Suzuki","year":"2017"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref50","article-title":"A simple but tough-to-beat baseline for sentence embeddings","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Arora","year":"2017"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1145\/3038912.3052569"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1145\/2783258.2783273"},{"key":"ref53","first-page":"718","article-title":"Variational mixture-of-experts autoencoders for multi-modal deep generative models","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Shi","year":"2019"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1007\/s10479-011-0841-3"}],"container-title":["IEEE Transactions on Multimedia"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6046\/9687854\/09535249.pdf?arnumber=9535249","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,11]],"date-time":"2024-01-11T22:51:12Z","timestamp":1705013472000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9535249\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":54,"URL":"https:\/\/doi.org\/10.1109\/tmm.2021.3111487","relation":{},"ISSN":["1520-9210","1941-0077"],"issn-type":[{"value":"1520-9210","type":"print"},{"value":"1941-0077","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]}}}