{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,4]],"date-time":"2024-07-04T17:33:42Z","timestamp":1720114422763},"reference-count":44,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2017,10,1]],"date-time":"2017-10-01T00:00:00Z","timestamp":1506816000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61673151","61503110"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Information Sciences"],"published-print":{"date-parts":[[2017,10]]},"DOI":"10.1016\/j.ins.2017.05.025","type":"journal-article","created":{"date-parts":[[2017,5,17]],"date-time":"2017-05-17T18:01:54Z","timestamp":1495044114000},"page":"122-135","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":39,"special_numbering":"C","title":["TIIREC: A tensor approach for tag-driven item recommendation with sparse user generated content"],"prefix":"10.1016","volume":"411","author":[{"given":"Lu","family":"Yu","sequence":"first","affiliation":[]},{"given":"Junming","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Ge","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Chuang","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Zi-Ke","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.ins.2017.05.025_bib0001","series-title":"Recommender Systems Handbook","first-page":"217","article-title":"Context-aware recommender systems, context-aware recommender systems","author":"Adomavicius","year":"2011"},{"key":"10.1016\/j.ins.2017.05.025_bib0002","series-title":"Proceedings of Advances in Neural Information Processing Systems","first-page":"64","article-title":"Polynomial semantic indexing","author":"Bai","year":"2009"},{"key":"10.1016\/j.ins.2017.05.025_bib0003","series-title":"Proceedings of the ACM Conference on Recommender Systems","first-page":"301","article-title":"Matrix factorization techniques for context aware recommendation","author":"Baltrunas","year":"2011"},{"key":"10.1016\/j.ins.2017.05.025_bib0004","series-title":"Proceedings of Advances in Neural Information Processing Systems","first-page":"2787","article-title":"Translating embeddings for modeling multi-relational data","author":"Bordes","year":"2013"},{"key":"10.1016\/j.ins.2017.05.025_bib0005","first-page":"993","article-title":"Latent dirichlet allocation","volume":"3","author":"Blei","year":"2003","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.ins.2017.05.025_bib0006","doi-asserted-by":"crossref","unstructured":"I. Cantador, P. Brusilovsky, T. Kuflik, Second workshop on information heterogeneity and fusion in recommender systems (hetrec2011), Proceedings of ACM Conference on Recommender Systems, Recsys (2011) 387\u2013388.","DOI":"10.1145\/2043932.2044016"},{"key":"10.1016\/j.ins.2017.05.025_bib0007","doi-asserted-by":"crossref","unstructured":"J.D. Carroll, J.-J. Chang, Analysis of Individual Differences in Multidimensional Scaling via an N-way Generalization of \u201cEckart-Young\u201d Decomposition 35 3(1970) 283\u2013319.","DOI":"10.1007\/BF02310791"},{"key":"10.1016\/j.ins.2017.05.025_bib0008","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1002\/(SICI)1097-4571(199009)41:6<391::AID-ASI1>3.0.CO;2-9","article-title":"Indexing by latent semantic analysis","volume":"41","author":"Deerwester","year":"1990","journal-title":"J. Am. Soc. Inf. Sci."},{"key":"10.1016\/j.ins.2017.05.025_bib0009","series-title":"Proceedings of the ACM Conference on Recommender Systems","first-page":"67","article-title":"Personalized, interactive tag recommendation for flickr","author":"Garg","year":"2008"},{"key":"10.1016\/j.ins.2017.05.025_bib0010","unstructured":"R.A. Harshman, Foundations of the Parafac procedure: Models and Conditions for an \u201cExplanatory\u201d Multimodal Factor Analysis (1970)."},{"key":"10.1016\/j.ins.2017.05.025_bib0011","series-title":"Proceedings of the ACM Conference on Recommender Systems","first-page":"9","article-title":"Query-driven context aware recommendation","author":"Hariri","year":"2013"},{"key":"10.1016\/j.ins.2017.05.025_bib0012","series-title":"Proceedings of the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval","first-page":"549","article-title":"Fast matrix factorization for online recommendation with implicit feedback","author":"He","year":"2016"},{"key":"10.1016\/j.ins.2017.05.025_bib0013","series-title":"Proceedings of the 7th International Conference on Web Search and Data Mining","first-page":"293","article-title":"Social collaborative retrieval","author":"Hsiao","year":"2014"},{"key":"10.1016\/j.ins.2017.05.025_bib0014","series-title":"Proceedings of European Conference on Principles of Data Mining and Knowledge Discovery","first-page":"506","article-title":"Tag recommendations in folksonomies","author":"J\u00e4schke","year":"2007"},{"key":"10.1016\/j.ins.2017.05.025_bib0015","series-title":"Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","first-page":"426","article-title":"Factorization meets the neighborhood: a multifaceted collaborative filtering model","author":"Koren","year":"2008"},{"key":"10.1016\/j.ins.2017.05.025_bib0016","series-title":"Proceedings of the IEEE International Conference on Data Engineering","first-page":"386","article-title":"Focused matrix factorization for audience selection in display advertising","author":"Kanagal","year":"2013"},{"key":"10.1016\/j.ins.2017.05.025_bib0017","series-title":"Proceedings of the ACM Conference on Recommender Systems","first-page":"79","article-title":"Multiverse recommendation: n-dimensional tensor factorization for context-aware collaborative filtering","author":"Karatzoglou","year":"2010"},{"issue":"8","key":"10.1016\/j.ins.2017.05.025_bib0018","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1109\/MC.2009.263","article-title":"Matrix factorization techniques for recommender systems","volume":"42","author":"Koren","year":"2009","journal-title":"Computer"},{"issue":"1","key":"10.1016\/j.ins.2017.05.025_bib0019","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1109\/MIC.2003.1167344","article-title":"Amazon.com recommendations: item-to-item collaborative filtering","volume":"7","author":"Linden","year":"2003","journal-title":"IEEE Internet Comput."},{"issue":"6755","key":"10.1016\/j.ins.2017.05.025_bib0020","doi-asserted-by":"crossref","first-page":"788","DOI":"10.1038\/44565","article-title":"Learning the parts of objects by non-negative matrix factorization","volume":"401","author":"Lee","year":"1999","journal-title":"Nature"},{"key":"10.1016\/j.ins.2017.05.025_bib0021","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.ins.2017.04.022","article-title":"Online pairwise learning algorithms with convex loss functions","volume":"406\u2013407","author":"Lin","year":"2017","journal-title":"Inf. Sci."},{"key":"10.1016\/j.ins.2017.05.025_bib0022","doi-asserted-by":"crossref","first-page":"467","DOI":"10.1016\/j.eswa.2016.08.009","article-title":"Large-scale recommender system with compact latent factor model","volume":"64","author":"Liu","year":"2016","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.ins.2017.05.025_bib0023","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1016\/j.knosys.2012.07.016","article-title":"Applying the learning rate adaptation to the matrix factorization based collaborative filtering","volume":"37","author":"Luo","year":"2013","journal-title":"Knowl. Based Syst."},{"key":"10.1016\/j.ins.2017.05.025_bib0024","series-title":"Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","first-page":"141","article-title":"Response prediction using collaborative filtering with hierarchies and side-information","author":"Menon","year":"2011"},{"issue":"5","key":"10.1016\/j.ins.2017.05.025_bib0025","doi-asserted-by":"crossref","first-page":"462","DOI":"10.1109\/TMM.2010.2051360","article-title":"Bridging the semantic gap between image contents and tags","volume":"12","author":"Ma","year":"2010","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.ins.2017.05.025_bib0026","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.ins.2015.10.044","article-title":"Mixed factorization for collaborative recommendation with heterogeneous explicit feedbacks","volume":"332","author":"Pan","year":"2016","journal-title":"Inf. Sci."},{"key":"10.1016\/j.ins.2017.05.025_bib0027","series-title":"Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","first-page":"727","article-title":"Alexandros nanopoulos, lars schmidt-thieme, learning optimal ranking with tensor factorization for tag recommendation","author":"Rendle","year":"2009"},{"key":"10.1016\/j.ins.2017.05.025_bib0028","series-title":"Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence","first-page":"452","article-title":"Lars schmidt-thieme, BPR: Bayesian personalized ranking from implicit feedback","author":"Rendle","year":"2009"},{"key":"10.1016\/j.ins.2017.05.025_bib0029","series-title":"Proceedings of the 3rd International Conference on Web search and Data Mining","first-page":"81","article-title":"Pairwise interaction tensor factorization for personalized tag recommendation","author":"Rendle","year":"2010"},{"key":"10.1016\/j.ins.2017.05.025_bib0030","series-title":"Proceedings of the 7th International Conference on Web Search and Data Mining","first-page":"273","article-title":"Improving pairwise learning for item recommendation from implicit feedback","author":"Rendle","year":"2014"},{"issue":"11","key":"10.1016\/j.ins.2017.05.025_bib0031","doi-asserted-by":"crossref","first-page":"992","DOI":"10.14778\/3402707.3402736","article-title":"Pathsim: meta path-based top-k similarity search in heterogeneous information networks","volume":"4","author":"Sun","year":"2011","journal-title":"Proc. VLDB Endow."},{"key":"10.1016\/j.ins.2017.05.025_bib0032","series-title":"Proceedings of Neural Information Processing Systems","article-title":"Probabilistic matrix factorization","author":"Salakhutdinov","year":"2007"},{"key":"10.1016\/j.ins.2017.05.025_bib0033","series-title":"Proceedings of the Conference on Recommender systems","first-page":"43","article-title":"Tag recommendations based on tensor dimensionality reduction","author":"Symeonidis","year":"2008"},{"key":"10.1016\/j.ins.2017.05.025_bib0034","series-title":"Proceedings of the 10th International Conference on World Wide Web","first-page":"285","article-title":"Item-based collaborative filtering recommendation algorithms","author":"Sarwar","year":"2001"},{"issue":"3","key":"10.1016\/j.ins.2017.05.025_bib0035","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1007\/BF02289464","article-title":"Some mathematical notes on three-mode factor analysis","volume":"31","author":"Tucker","year":"1966","journal-title":"Psychometrika"},{"issue":"1","key":"10.1016\/j.ins.2017.05.025_bib0036","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1007\/s10994-010-5198-3","article-title":"Large scale image annotation: learning to rank with joint word-image embeddings","volume":"81","author":"Weston","year":"2010","journal-title":"Mach. Learn."},{"key":"10.1016\/j.ins.2017.05.025_bib0037","series-title":"Proceedings of the 29th International Conference on Machine Learning","first-page":"9","article-title":"Latent collaborative retrieval","author":"Weston","year":"2012"},{"key":"10.1016\/j.ins.2017.05.025_bib0038","series-title":"Proceedings of SIAM International Conference on Data Mining","first-page":"211","article-title":"Temporal collaborative filtering with Bayesian probabilistic tensor factorization","author":"Xiong","year":"2010"},{"key":"10.1016\/j.ins.2017.05.025_bib0039","series-title":"Proceedings of the 7th International Conference on Web Search and Data Mining","first-page":"283","article-title":"Personalized entity recommendation: a heterogeneous information network approach","author":"Yu","year":"2014"},{"key":"10.1016\/j.ins.2017.05.025_bib0040","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1016\/j.knosys.2015.05.016","article-title":"Multi-linear interactive matrix factorization","volume":"85","author":"Yu","year":"2015","journal-title":"Knowl. Based Syst."},{"key":"10.1016\/j.ins.2017.05.025_bib0041","series-title":"Proceedings of 17th International Conference on Web-Age Information Management","first-page":"244","article-title":"RankMBPR: rank-aware mutual bayesian personalized ranking for item recommendation","author":"Yu","year":"2016"},{"key":"10.1016\/j.ins.2017.05.025_bib0042","series-title":"Proceedings of the 17th SIAM International Conference on Data Mining","article-title":"User collaborative network embedding for social recommender systems","author":"Zhang","year":"2017"},{"key":"10.1016\/j.ins.2017.05.025_bib0043","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.physrep.2016.07.002","article-title":"Dynamics of information diffusion and its applications on complex networks","volume":"651","author":"Zhang","year":"2016","journal-title":"Phys. Rep."},{"key":"10.1016\/j.ins.2017.05.025_bib0044","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/j.ins.2014.12.004","article-title":"GPUTENSOR: efficient tensor factorization for context-aware recommendations","volume":"299","author":"Zou","year":"2015","journal-title":"Inf. Sci."}],"container-title":["Information Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S002002551730734X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S002002551730734X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2020,10,8]],"date-time":"2020-10-08T00:19:58Z","timestamp":1602116398000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S002002551730734X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,10]]},"references-count":44,"alternative-id":["S002002551730734X"],"URL":"https:\/\/doi.org\/10.1016\/j.ins.2017.05.025","relation":{},"ISSN":["0020-0255"],"issn-type":[{"value":"0020-0255","type":"print"}],"subject":[],"published":{"date-parts":[[2017,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"TIIREC: A tensor approach for tag-driven item recommendation with sparse user generated content","name":"articletitle","label":"Article Title"},{"value":"Information Sciences","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ins.2017.05.025","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2017 Elsevier Inc. All rights reserved.","name":"copyright","label":"Copyright"}]}}