{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T11:19:18Z","timestamp":1762341558740,"version":"3.37.3"},"reference-count":37,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2020,12,10]],"date-time":"2020-12-10T00:00:00Z","timestamp":1607558400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,12,10]],"date-time":"2020-12-10T00:00:00Z","timestamp":1607558400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Data Min Knowl Disc"],"published-print":{"date-parts":[[2021,3]]},"DOI":"10.1007\/s10618-020-00723-7","type":"journal-article","created":{"date-parts":[[2020,12,10]],"date-time":"2020-12-10T08:02:44Z","timestamp":1607587364000},"page":"505-532","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Variational auto-encoder based Bayesian Poisson tensor factorization for sparse and imbalanced count data"],"prefix":"10.1007","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4502-8472","authenticated-orcid":false,"given":"Yuan","family":"Jin","sequence":"first","affiliation":[]},{"given":"Ming","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Yunfeng","family":"Li","sequence":"additional","affiliation":[]},{"given":"Ruohua","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Lan","family":"Du","sequence":"additional","affiliation":[]},{"given":"Longxiang","family":"Gao","sequence":"additional","affiliation":[]},{"given":"Yong","family":"Xiang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,12,10]]},"reference":[{"issue":"1","key":"723_CR1","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/j.ins.2007.07.024","volume":"178","author":"HJ Ahn","year":"2008","unstructured":"Ahn HJ (2008) A new similarity measure for collaborative filtering to alleviate the new user cold-starting problem. Inf Sci 178(1):37\u201351","journal-title":"Inf Sci"},{"key":"723_CR2","unstructured":"Aletras N, Stevenson M (2013) Evaluating topic coherence using distributional semantics. In: Proceedings of the 10th international conference on computational semantics (IWCS 2013)\u2013Long Papers, pp 13\u201322"},{"key":"723_CR3","unstructured":"Buntine WL, Mishra S (2014) Experiments with non-parametric topic models. In: Proceedings of the 20th ACM SIGKDD international conference on knowledge discovery and data mining, pp 881\u2013890"},{"issue":"4","key":"723_CR4","doi-asserted-by":"publisher","first-page":"1272","DOI":"10.1137\/110859063","volume":"33","author":"EC Chi","year":"2012","unstructured":"Chi EC, Kolda TG (2012) On tensors, sparsity, and nonnegative factorizations. SIAM J Matrix Anal Appl 33(4):1272\u20131299","journal-title":"SIAM J Matrix Anal Appl"},{"key":"723_CR5","doi-asserted-by":"publisher","DOI":"10.1201\/9781420036121","volume-title":"Multidimensional scaling","author":"TF Cox","year":"2000","unstructured":"Cox TF, Cox MA (2000) Multidimensional scaling. Chapman and Hall\/CRC, Boca Raton"},{"key":"723_CR6","doi-asserted-by":"crossref","unstructured":"Deng Z, Navarathna R, Carr P, Mandt S, Yue Y, Matthews I, Mori G (2017) Factorized variational autoencoders for modeling audience reactions to movies. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2577\u20132586","DOI":"10.1109\/CVPR.2017.637"},{"key":"723_CR7","unstructured":"Figurnov M, Mohamed S, Mnih A (2018) Implicit reparameterization gradients. In: Advances in neural information processing systems, pp 441\u2013452"},{"issue":"4","key":"723_CR8","doi-asserted-by":"publisher","first-page":"631","DOI":"10.1080\/10556780801996244","volume":"23","author":"MP Friedlander","year":"2008","unstructured":"Friedlander MP, Hatz K (2008) Computing non-negative tensor factorizations. Optim Methods Softw 23(4):631\u2013647","journal-title":"Optim Methods Softw"},{"key":"723_CR9","unstructured":"Gopalan P, Hofman JM, Blei DM (2015) Scalable recommendation with hierarchical poisson factorization. In: Proceedings of the 31st conference on uncertainty in artificial intelligence, AUAI Press, UAI\u201915, pp 326\u2013335"},{"key":"723_CR10","doi-asserted-by":"crossref","unstructured":"He X, Liao L, Zhang H, Nie L, Hu X, Chua TS (2017) Neural collaborative filtering. In: Proceedings of the 26th international conference on world wide web, pp 173\u2013182","DOI":"10.1145\/3038912.3052569"},{"key":"723_CR11","doi-asserted-by":"crossref","unstructured":"He X, Du X, Wang X, Tian F, Tang J, Chua TS (2018) Outer product-based neural collaborative filtering. In: Proceedings of the 27th international joint conference on artificial intelligence, AAAI Press, IJCAI\u201918, pp 2227\u20132233","DOI":"10.24963\/ijcai.2018\/308"},{"key":"723_CR12","unstructured":"Hidasi B, Karatzoglou A, Baltrunas L, Tikk D (2016) Session-based recommendations with recurrent neural networks. In: Proceedings of the 4th international conference on learning representations, ICLR 2016, San Juan, Puerto Rico, May 2\u20134, 2016, conference track proceedings"},{"key":"723_CR13","doi-asserted-by":"publisher","unstructured":"Hinrich JL, Nielsen SFV, Madsen KH, M\u00f8rup M (2018) Variational Bayesian partially observed non-negative tensor factorization. In: 2018 IEEE 28th international workshop on machine learning for signal processing (MLSP), pp 1\u20136. https:\/\/doi.org\/10.1109\/MLSP.2018.8516924","DOI":"10.1109\/MLSP.2018.8516924"},{"issue":"8","key":"723_CR14","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural Comput 9(8):1735\u20131780","journal-title":"Neural Comput"},{"key":"723_CR15","doi-asserted-by":"crossref","unstructured":"Hu C, Rai P, Chen C, Harding M, Carin L (2015) Scalable Bayesian non-negative tensor factorization for massive count data. In: Machine learning and knowledge discovery in databases. Springer International Publishing, pp 53\u201370","DOI":"10.1007\/978-3-319-23525-7_4"},{"key":"723_CR16","doi-asserted-by":"crossref","unstructured":"Hu Y, Koren Y, Volinsky C (2008) Collaborative filtering for implicit feedback datasets. In: 2008 Eighth IEEE international conference on data mining, IEEE, pp 263\u2013272","DOI":"10.1109\/ICDM.2008.22"},{"key":"723_CR17","unstructured":"Jankowiak M, Obermeyer F (2018) Pathwise derivatives beyond the reparameterization trick. In: International conference on machine learning, pp 2240\u20132249"},{"key":"723_CR18","doi-asserted-by":"crossref","unstructured":"Kim D, Park C, Oh J, Lee S, Yu H (2016) Convolutional matrix factorization for document context-aware recommendation. In: Proceedings of the 10th ACM conference on recommender systems, ACM, RecSys \u201916, pp 233\u2013240","DOI":"10.1145\/2959100.2959165"},{"key":"723_CR19","unstructured":"Kingma DP, Ba J (2014) Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980"},{"key":"723_CR20","unstructured":"Kingma DP, Welling M (2014) Auto-encoding variational bayes. In: Proceedings of the 2nd international conference on learning representations (ICLR)"},{"key":"723_CR21","unstructured":"Knowles DA (2015) Stochastic gradient variational bayes for gamma approximating distributions. arXiv preprint arXiv:1509.01631"},{"issue":"3","key":"723_CR22","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1137\/07070111X","volume":"51","author":"TG Kolda","year":"2009","unstructured":"Kolda TG, Bader BW (2009) Tensor decompositions and applications. SIAM Rev 51(3):455\u2013500","journal-title":"SIAM Rev"},{"key":"723_CR23","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2012) Imagenet classification with deep convolutional neural networks. In: Pereira F, Burges CJC, Bottou L, Weinberger KQ (eds) Advances in neural information processing systems 25, Curran Associates, Inc., pp 1097\u20131105. http:\/\/papers.nips.cc\/paper\/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf"},{"key":"723_CR24","doi-asserted-by":"crossref","unstructured":"Li S, Kawale J, Fu Y (2015) Deep collaborative filtering via marginalized denoising auto-encoder. In: Proceedings of the 24th ACM international on conference on information and knowledge management, ACM, CIKM \u201915, pp 811\u2013820","DOI":"10.1145\/2806416.2806527"},{"key":"723_CR25","doi-asserted-by":"crossref","unstructured":"Liu H, Li Y, Tsang M, Liu Y (2019) Costco: a neural tensor completion model for sparse tensors. In: Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery and data mining, Association for Computing Machinery, pp 324\u2013334","DOI":"10.1145\/3292500.3330881"},{"issue":"2","key":"723_CR26","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1145\/1540276.1540302","volume":"10","author":"AM Rashid","year":"2008","unstructured":"Rashid AM, Karypis G, Riedl J (2008) Learning preferences of new users in recommender systems: an information theoretic approach. ACM SIGKDD Explor Newsl 10(2):90\u2013100","journal-title":"ACM SIGKDD Explor Newsl"},{"key":"723_CR27","doi-asserted-by":"crossref","unstructured":"Schein A, Paisley J, Blei DM, Wallach H (2015) Bayesian Poisson tensor factorization for inferring multilateral relations from sparse dyadic event counts. In: Proceedings of the 21th ACM SIGKDD international conference on knowledge discovery and data mining, ACM, pp 1045\u20131054","DOI":"10.1145\/2783258.2783414"},{"key":"723_CR28","unstructured":"Schein A, Zhou M, Blei DM, Wallach H (2016) Bayesian Poisson tucker decomposition for learning the structure of international relations. In: Proceedings of the 33rd international conference on international conference on machine learning\u2014volume 48, JMLR.org, ICML\u201916, pp 2810\u20132819. http:\/\/dl.acm.org\/citation.cfm?id=3045390.3045686"},{"key":"723_CR29","unstructured":"Schmidt MN, Mohamed S (2009) Probabilistic non-negative tensor factorization using Markov chain Monte Carlo. In: 2009 17th European signal processing conference, IEEE, pp 1918\u20131922"},{"key":"723_CR30","doi-asserted-by":"crossref","unstructured":"Sedhain S, Menon AK, Sanner S, Xie L (2015) Autorec: autoencoders meet collaborative filtering. In: Proceedings of the 24th international conference on world wide web, ACM, WWW \u201915 Companion, pp 111\u2013112","DOI":"10.1145\/2740908.2742726"},{"key":"723_CR31","doi-asserted-by":"crossref","unstructured":"Shashua A, Hazan T (2005) Non-negative tensor factorization with applications to statistics and computer vision. In: Proceedings of the 22nd international conference on machine learning, ACM, pp 792\u2013799","DOI":"10.1145\/1102351.1102451"},{"issue":"12","key":"723_CR32","doi-asserted-by":"publisher","first-page":"1255","DOI":"10.1016\/S0167-8655(01)00070-8","volume":"22","author":"M Welling","year":"2001","unstructured":"Welling M, Weber M (2001) Positive tensor factorization. Pattern Recogn Lett 22(12):1255\u20131261","journal-title":"Pattern Recogn Lett"},{"key":"723_CR33","doi-asserted-by":"publisher","unstructured":"Wu X, Shi B, Dong Y, Huang C, Chawla NV (2019) Neural tensor factorization for temporal interaction learning. In: Proceedings of the twelfth ACM international conference on web search and data mining, Association for Computing Machinery, New York, NY, USA, WSDM \u201919, pp 537\u2013545. https:\/\/doi.org\/10.1145\/3289600.3290998","DOI":"10.1145\/3289600.3290998"},{"key":"723_CR34","doi-asserted-by":"crossref","unstructured":"Xue HJ, Dai X, Zhang J, Huang S, Chen J (2017) Deep matrix factorization models for recommender systems. In: Proceedings of the 26th international joint conference on artificial intelligence, IJCAI-17, pp 3203\u20133209","DOI":"10.24963\/ijcai.2017\/447"},{"key":"723_CR35","doi-asserted-by":"crossref","unstructured":"Yu Y, Zhang L, Wang C, Gao R, Zhao W Jiang J (2019) Neural personalized ranking via Poisson factor model for item recommendation. Complexity","DOI":"10.1155\/2019\/3563674"},{"issue":"1","key":"723_CR36","first-page":"5:1","volume":"52","author":"S Zhang","year":"2019","unstructured":"Zhang S, Yao L, Sun A, Tay Y (2019) Deep learning based recommender system: a survey and new perspectives. ACM Comput Surv 52(1):5:1\u20135:38","journal-title":"ACM Comput Surv"},{"key":"723_CR37","unstructured":"Zhou M, Hannah L, Dunson D, Carin L (2012) Beta-negative binomial process and poisson factor analysis. In: Proceedings of the 15th international conference on artificial intelligence and statistics, PMLR, Proceedings of Machine Learning Research, vol\u00a022, pp 1462\u20131471"}],"container-title":["Data Mining and Knowledge Discovery"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10618-020-00723-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10618-020-00723-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10618-020-00723-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,2,21]],"date-time":"2021-02-21T05:44:50Z","timestamp":1613886290000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10618-020-00723-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12,10]]},"references-count":37,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2021,3]]}},"alternative-id":["723"],"URL":"https:\/\/doi.org\/10.1007\/s10618-020-00723-7","relation":{},"ISSN":["1384-5810","1573-756X"],"issn-type":[{"type":"print","value":"1384-5810"},{"type":"electronic","value":"1573-756X"}],"subject":[],"published":{"date-parts":[[2020,12,10]]},"assertion":[{"value":"29 February 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 November 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 December 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}