{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T07:02:05Z","timestamp":1780383725496,"version":"3.54.1"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,4,4]],"date-time":"2020-04-04T00:00:00Z","timestamp":1585958400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,4,4]],"date-time":"2020-04-04T00:00:00Z","timestamp":1585958400000},"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":["Inf Syst Front"],"published-print":{"date-parts":[[2021,2]]},"DOI":"10.1007\/s10796-020-10005-8","type":"journal-article","created":{"date-parts":[[2020,4,4]],"date-time":"2020-04-04T17:04:18Z","timestamp":1586019858000},"page":"53-69","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Multi-view Latent Learning Applied to Fashion Industry"],"prefix":"10.1007","volume":"23","author":[{"given":"Giovanni Battista","family":"Gardino","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rosa","family":"Meo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giuseppe","family":"Craparotta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,4,4]]},"reference":[{"key":"10005_CR1","unstructured":"Adegeest, N. (2016). The dynamics of fashion trend forecasting."},{"key":"10005_CR2","unstructured":"Al-Halah, Z., Stiefelhagen, R., Grauman, K. (2017). Fashion forward: forecasting visual style in fashion. arXiv:1705.06394."},{"issue":"3","key":"10005_CR3","doi-asserted-by":"publisher","first-page":"549","DOI":"10.1093\/biomet\/85.3.549","volume":"85","author":"A Basu","year":"1998","unstructured":"Basu, A., Harris, I.R.N., Hjort, L., Jones, M.C. (1998). Robust and efficient estimation by minimising a density power divergence. Biometrika, 85(3), 549\u2013559.","journal-title":"Biometrika"},{"issue":"2","key":"10005_CR4","doi-asserted-by":"publisher","first-page":"1654","DOI":"10.1016\/j.eswa.2009.06.087","volume":"37","author":"C Ching-Chin","year":"2010","unstructured":"Ching-Chin, C., Ieng, A.I.K., Ling-Ling, W., Ling-Chieh, K. (2010). Designing a decision-support system for new product sales forecasting. Expert Systems with Applications, 37(2), 1654\u20131665. ISSN 0957-4174. http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0957417409006034.","journal-title":"Expert Systems with Applications"},{"issue":"3","key":"10005_CR5","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1016\/S0925-5273(03)00068-9","volume":"86","author":"C-W Chu","year":"2003","unstructured":"Chu, C.-W., & Zhang, G.P. (2003). A comparative study of linear and nonlinear models for aggregate retail sales forecasting. International Journal of Production Economics, 86(3), 217\u2013231. ISSN 0925-5273. http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0925527303000689.","journal-title":"International Journal of Production Economics"},{"key":"10005_CR6","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.promfg.2015.07.014","volume":"2","author":"W Dai","year":"2015","unstructured":"Dai, W., Chuang, Y.-Y., Lu, C.-J. (2015). A clustering-based sales forecasting scheme using support vector regression for computer server. Procedia Manufacturing, 2, 82\u201386.","journal-title":"Procedia Manufacturing"},{"key":"10005_CR7","unstructured":"Demetters, T. (2018). Understanding convolutions. http:\/\/timdettmers.com\/2015\/03\/26\/convolution-deep-learning\/."},{"key":"10005_CR8","unstructured":"Ding, Z., & Fu, Y. (2016). Robust multi-view subspace learning through dual low-rank decompositions. https:\/\/www.aaai.org\/ocs\/index.php\/AAAI\/AAAI16\/paper\/view\/11952."},{"key":"10005_CR9","unstructured":"Edosio, U.Z. (2014). Big data analytics and its application in e-commerce. Proceedings E-Commerce Technologies. University of Bradford."},{"key":"10005_CR10","unstructured":"Erhard, J., & Bug, P. (2016). Application of predictive analytics to sales forecasting in fashion business."},{"issue":"3","key":"10005_CR11","doi-asserted-by":"publisher","first-page":"483","DOI":"10.1057\/jors.2010.40","volume":"62","author":"R Fildes","year":"2011","unstructured":"Fildes, R., & Kingsman, B. (2011). Incorporating demand uncertainty and forecast error in supply chain planning models. Journal of the Operational Research Society, 62(3), 483\u2013500. ISSN 1476-9360. https:\/\/doi.org\/10.1057\/jors.2010.40.","journal-title":"Journal of the Operational Research Society"},{"key":"10005_CR12","unstructured":"Gao, J., Han, J., Liu, J., Wang, C.C. (2013). Multi-view clustering via joint nonnegative matrix factorization. In SDM."},{"issue":"1","key":"10005_CR13","first-page":"5","volume":"14","author":"SR Gunn","year":"1998","unstructured":"Gunn, S.R., & et al. (1998). Support vector machines for classification and regression. ISIS Technical Report, 14(1), 5\u201316.","journal-title":"ISIS Technical Report"},{"issue":"12","key":"10005_CR14","doi-asserted-by":"publisher","first-page":"2639","DOI":"10.1162\/0899766042321814","volume":"16","author":"DR Hardoon","year":"2004","unstructured":"Hardoon, D.R., Szedmak, S., Shawe-Taylor, J. (2004). Canonical correlation analysis: an overview with application to learning methods. Neural Computation, 16(12), 2639\u20132664. https:\/\/doi.org\/10.1162\/0899766042321814.","journal-title":"Neural Computation"},{"key":"10005_CR15","unstructured":"Jagadeesh, V., Piramuthu, R., Bhardwaj, A., Di, W., Sundaresan, N. (2014). Large scale visual recommendations from street fashion images. In Proceedings of the 20th ACM SIGKDD international conference on knowledge discovery and data mining (pp. 1925\u20131934): ACM."},{"key":"10005_CR16","unstructured":"Kusakunniran, W., Wu, Q., Zhang, J., Li, H. (2010). Support vector regression for multi-view gait recognition based on local motion feature selection. In 2010 IEEE conference on computer vision and pattern recognition (CVPR) (pp. 974\u2013981): IEEE."},{"issue":"6755","key":"10005_CR17","doi-asserted-by":"publisher","first-page":"788","DOI":"10.1038\/44565","volume":"401","author":"DD Lee","year":"1999","unstructured":"Lee, D.D., & Seung, H.S. (1999). Learning the parts of objects by non-negative matrix factorization. Nature, 401(6755), 788\u2013 91.","journal-title":"Nature"},{"key":"10005_CR18","unstructured":"Li, Y., Gong, S., Liddell, H. (2000). Support vector regression and classification based multi-view face detection and recognition. In Fourth IEEE international conference on automatic face and gesture recognition proceedings (pp. 300\u2013305): IEEE."},{"key":"10005_CR19","unstructured":"Liu, M., Luo, Y., Tao, D., Xu, C., Wen, Y. (2015). Low-rank multi-view learning in matrix completion for multi-label image classification. https:\/\/www.aaai.org\/ocs\/index.php\/AAAI\/AAAI15\/paper\/view\/9341."},{"key":"10005_CR20","unstructured":"Na, L., Ren, S., Choi, T.-M., Hui, C.-L., Ng, S.-F. (2013). Sales forecasting for fashion retailing service industry: a review. Mathematical Problems in Engineering, 2013."},{"key":"10005_CR21","unstructured":"Officer, Z., & Inditex, S.A. (2009). Zara uses operations research to reengineer its global distribution process."},{"key":"10005_CR22","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1016\/0024-3795(92)90229-4","volume":"165","author":"KM Prasad","year":"1992","unstructured":"Prasad, K.M., & Bapat, R.B. (1992). The generalized moore-penrose inverse. Linear Algebra and its Applications, 165, 59\u201369.","journal-title":"Linear Algebra and its Applications"},{"key":"10005_CR23","doi-asserted-by":"crossref","unstructured":"Rastogi, P., Van Durme, B., Arora, R. (2015). Multiview lsa: representation learning via generalized cca. In HLT-NAACL.","DOI":"10.3115\/v1\/N15-1058"},{"key":"10005_CR24","unstructured":"Sawyer, S. (2006). Generalized inverses: how to invert a non-invertible matrix."},{"key":"10005_CR25","first-page":"2012","volume":"26","author":"DM Smith","year":"2010","unstructured":"Smith, D.M., & William, M.L. (2010). Data loss and hard drive failure: understanding the causes and costs. Retrieved February, 26, 2012.","journal-title":"Retrieved February"},{"key":"10005_CR26","unstructured":"Smola, A.J., & et al. (1996). Regression estimation with support vector learning machines. PhD thesis, Master\u2019s thesis, T. Univ. M\u00fcnchen."},{"key":"10005_CR27","doi-asserted-by":"publisher","unstructured":"Sp\u00e4th, H. (1981). The minisum location problem for the jaccard metric. Operations-Research-Spektrum 3(2). ISSN 1436-6304. https:\/\/doi.org\/10.1007\/BF01720100.","DOI":"10.1007\/BF01720100"},{"issue":"2","key":"10005_CR28","doi-asserted-by":"publisher","first-page":"470","DOI":"10.1016\/j.ijpe.2010.07.018","volume":"128","author":"S Thomassey","year":"2010","unstructured":"Thomassey, S. (2010). Sales forecasts in clothing industry: the key success factor of the supply chain management. International Journal of Production Economics, 128(2), 470\u2013483.","journal-title":"International Journal of Production Economics"},{"key":"10005_CR29","unstructured":"Thomassey, S. (2014). Sales forecasting in apparel and fashion industry: a review. In Intelligent fashion forecasting systems: models and applications (pp. 9\u201327). Berlin: Springer."},{"issue":"1","key":"10005_CR30","doi-asserted-by":"publisher","first-page":"408","DOI":"10.1016\/j.dss.2005.01.008","volume":"42","author":"S Thomassey","year":"2006","unstructured":"Thomassey, S., & Fiordaliso, A. (2006). A hybrid sales forecasting system based on clustering and decision trees. Decision Support Systems, 42(1), 408\u2013421.","journal-title":"Decision Support Systems"},{"key":"10005_CR31","unstructured":"Yin, M., Gao, J., Xie, S., Guo, Y. (2016). Low-rank multi-view clustering in third-order tensor space. CoRR, arXiv:1608.08336."},{"key":"10005_CR32","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/j.inffus.2017.02.007","volume":"3","author":"J Zhao","year":"2017","unstructured":"Zhao, J., Xie, X., Xu, X., Sun, S. (2017). Multi-view learning overview: recent progress and new challenges. Information Fusion, 3, 43\u201354. ISSN 1566-2535. http:\/\/www.sciencedirect.com\/science\/article\/pii\/S1566253516302032.","journal-title":"Information Fusion"}],"container-title":["Information Systems Frontiers"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10796-020-10005-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10796-020-10005-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10796-020-10005-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,4,3]],"date-time":"2021-04-03T23:10:29Z","timestamp":1617491429000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10796-020-10005-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4,4]]},"references-count":32,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,2]]}},"alternative-id":["10005"],"URL":"https:\/\/doi.org\/10.1007\/s10796-020-10005-8","relation":{},"ISSN":["1387-3326","1572-9419"],"issn-type":[{"value":"1387-3326","type":"print"},{"value":"1572-9419","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,4,4]]},"assertion":[{"value":"4 April 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}