{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T20:01:10Z","timestamp":1769976070605,"version":"3.49.0"},"reference-count":44,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2020,8,1]],"date-time":"2020-08-01T00:00:00Z","timestamp":1596240000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/www.elsevier.com\/legal\/tdmrep-license"}],"funder":[{"DOI":"10.13039\/501100004193","name":"Nanjing University of Aeronautics and Astronautics","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100004193","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":[[2020,8]]},"DOI":"10.1016\/j.ins.2020.03.062","type":"journal-article","created":{"date-parts":[[2020,4,30]],"date-time":"2020-04-30T12:47:08Z","timestamp":1588250828000},"page":"68-86","update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":12,"special_numbering":"C","title":["A deep neural network of multi-form alliances for personalized recommendations"],"prefix":"10.1016","volume":"531","author":[{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-5882-9562","authenticated-orcid":false,"given":"Xuna","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingmei","family":"Tan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lifan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.ins.2020.03.062_bib0001","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.dss.2015.03.008","article-title":"Recommender system application developments: a survey","volume":"74","author":"Lu","year":"2015","journal-title":"Decis. Support Syst."},{"key":"10.1016\/j.ins.2020.03.062_bib0002","doi-asserted-by":"crossref","first-page":"302","DOI":"10.1016\/j.ins.2015.02.003","article-title":"Recommending blog articles based on popular event trend analysis","volume":"305","author":"Liu","year":"2015","journal-title":"Inf. Sci."},{"key":"10.1016\/j.ins.2020.03.062_bib0003","article-title":"Do recommender systems benefit users? A modeling approach","volume":"4","author":"Yeung","year":"2016","journal-title":"J. Stat. Mech. Theory Exp."},{"key":"10.1016\/j.ins.2020.03.062_bib0004","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2019.105131","article-title":"A T1OWA fuzzy linguistic aggregation methodology for searching feature-based opinions","volume":"189","author":"Serrano-Guerrero","year":"2020","journal-title":"Knowl. Based Syst."},{"key":"10.1016\/j.ins.2020.03.062_bib0005","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1007\/s12525-016-0228-z","article-title":"Predicting user behavior in electronic markets based on personality-mining in large online social networks","volume":"27","author":"Buettner","year":"2016","journal-title":"Electron. Mark."},{"key":"10.1016\/j.ins.2020.03.062_bib0006","series-title":"Proceedings of the 8th ACM Conference on Recommender Systems","first-page":"293","article-title":"Convex AUC optimization for top-n recommendation with implicit feedback","author":"Aiolli","year":"2014"},{"key":"10.1016\/j.ins.2020.03.062_bib0007","series-title":"Proceedings of IEEE Transactions on Cybernetics","first-page":"1","article-title":"A novel deep learning-based collaborative filtering model for recommendation system","author":"Fu","year":"2018"},{"key":"10.1016\/j.ins.2020.03.062_bib0008","series-title":"Proceedings of the 26th International World Wide Web Conference","first-page":"173","article-title":"Neural collaborative filtering","author":"He","year":"2017"},{"key":"10.1016\/j.ins.2020.03.062_bib0009","doi-asserted-by":"crossref","first-page":"2811","DOI":"10.1109\/TGRS.2017.2783902","article-title":"When deep learning meets metric learning: remote sensing image scene classification via learning discriminative CNNs","volume":"56","author":"Cheng","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.ins.2020.03.062_bib0010","doi-asserted-by":"crossref","first-page":"1552","DOI":"10.1016\/j.ins.2011.01.005","article-title":"Personalized recommendation of popular blog articles for mobile applications","volume":"181","author":"Liu","year":"2011","journal-title":"Inf. Sci."},{"key":"10.1016\/j.ins.2020.03.062_bib0011","series-title":"Proceedings of International Conference on Information Science and Applications","first-page":"451","article-title":"Deep learning based recommendation: a survey","author":"Liu","year":"2017"},{"key":"10.1016\/j.ins.2020.03.062_bib0012","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1007\/s10115-018-1154-5","article-title":"Personalized recommendation with implicit feedback via learning pairwise preferences over item-sets","volume":"58","author":"Pan","year":"2019","journal-title":"Knowl. Inf. Syst."},{"key":"10.1016\/j.ins.2020.03.062_bib0013","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1016\/j.ins.2013.06.009","article-title":"Hiperion: a fuzzy approach for recommending educational activities based on the acquisition of competences","volume":"248","author":"Serrano-Guerrero","year":"2013","journal-title":"Inf. Sci."},{"key":"10.1016\/j.ins.2020.03.062_bib0014","doi-asserted-by":"crossref","first-page":"1503","DOI":"10.1016\/j.ins.2011.01.012","article-title":"A google wave-based fuzzy recommender system to disseminate information in university digital libraries 2.0","volume":"181","author":"Serrano-Guerrero","year":"2011","journal-title":"Inf. Sci."},{"key":"10.1016\/j.ins.2020.03.062_bib0015","doi-asserted-by":"crossref","first-page":"2228","DOI":"10.1109\/TKDE.2018.2821174","article-title":"A general framework for implicit and explicit social recommendation","volume":"30","author":"Hsu","year":"2018","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"10.1016\/j.ins.2020.03.062_bib0016","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1016\/j.knosys.2015.12.018","article-title":"A non-negative matrix factorization for collaborative filtering recommender systems based on a Bayesian probabilistic model","volume":"97","author":"Hernando","year":"2016","journal-title":"Knowl. Based Syst."},{"key":"10.1016\/j.ins.2020.03.062_bib0017","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.ins.2013.03.041","article-title":"Recommending social network applications via social filtering mechanisms","volume":"239","author":"Li","year":"2013","journal-title":"Inf. Sci."},{"key":"10.1016\/j.ins.2020.03.062_bib0018","doi-asserted-by":"crossref","first-page":"1171","DOI":"10.1016\/j.ipm.2017.05.003","article-title":"Item-network-based collaborative filtering: a personalized recommendation method based on a user's item network","volume":"53","author":"Ha","year":"2017","journal-title":"Inf. Process Manag."},{"key":"10.1016\/j.ins.2020.03.062_bib0019","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3137597.3137599","article-title":"Collaborative filtering for binary, positiveonly data","volume":"19","author":"Verstrepen","year":"2017","journal-title":"ACM Sigkdd Explor. Newsl."},{"key":"10.1016\/j.ins.2020.03.062_bib0020","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/j.ins.2019.07.083","article-title":"A collective filtering based content transmission scheme in edge of vehicles","volume":"506","author":"Wang","year":"2019","journal-title":"Inf. Sci."},{"key":"10.1016\/j.ins.2020.03.062_bib0021","doi-asserted-by":"crossref","first-page":"535","DOI":"10.1016\/j.ins.2019.07.093","article-title":"Sparse online collaborative filtering with dynamic regularization","volume":"505","author":"Li","year":"2019","journal-title":"Inf. Sci."},{"key":"10.1016\/j.ins.2020.03.062_bib0022","first-page":"164","article-title":"Adaptive nonnegative matrix factorization and measure comparisons for recommender systems","volume":"354","author":"Del Corso","year":"2019","journal-title":"Appl. Math. Comput."},{"key":"10.1016\/j.ins.2020.03.062_bib0023","doi-asserted-by":"crossref","first-page":"3121","DOI":"10.1007\/s11277-018-5332-2","article-title":"An improved neighborhood-aware unified probabilistic matrix factorization recommendation","volume":"102","author":"Cao","year":"2018","journal-title":"Wirel. Pers. Commun."},{"key":"10.1016\/j.ins.2020.03.062_bib0024","series-title":"A Neural Autoregressive Approach to Collaborative Filtering","first-page":"764","author":"Zheng","year":"2016"},{"key":"10.1016\/j.ins.2020.03.062_bib0025","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1016\/j.eswa.2018.11.003","article-title":"Personalized recommendation by matrix co-factorization with tags and time information","volume":"119","author":"Luo","year":"2018","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.ins.2020.03.062_bib0026","doi-asserted-by":"crossref","first-page":"6785","DOI":"10.1007\/s00500-018-3406-4","article-title":"A time-sensitive personalized recommendation method based on probabilistic matrix factorization technique","volume":"22","author":"Xiao","year":"2018","journal-title":"Soft Comput."},{"key":"10.1016\/j.ins.2020.03.062_bib0027","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.eswa.2018.07.065","article-title":"EMD2FNN: a strategy combining empirical mode decomposition and factorization machine based neural network for stock market trend prediction","volume":"115","author":"Zhou","year":"2018","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.ins.2020.03.062_bib0028","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1080\/14697688.2018.1521002","article-title":"Exploiting social media with higher-order factorization machines: statistical arbitrage on high-frequency data of the S&P 500","volume":"19","author":"Knoll","year":"2019","journal-title":"Quant. Financ."},{"key":"10.1016\/j.ins.2020.03.062_bib0029","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1016\/j.ins.2019.07.024","article-title":"Deep latent factor model with hierarchical similarity measure for recommender systems","volume":"503","author":"Han","year":"2019","journal-title":"Inf. Sci."},{"key":"10.1016\/j.ins.2020.03.062_bib0030","doi-asserted-by":"crossref","first-page":"276","DOI":"10.1109\/TIP.2016.2624140","article-title":"Weakly-supervised deep matrix factorization for social image understanding","volume":"26","author":"Li","year":"2016","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.ins.2020.03.062_bib0031","doi-asserted-by":"crossref","first-page":"4973","DOI":"10.1109\/TIE.2017.2767540","article-title":"LiftingNet: a novel deep learning network with layerwise feature learning from noisy mechanical data for fault classification","volume":"65","author":"Pan","year":"2017","journal-title":"IEEE Trans. Ind. Electron."},{"key":"10.1016\/j.ins.2020.03.062_bib0032","series-title":"Proceedings of the 8th IEEE\/ACM International Conference on Advances in Social Networks Analysis and Mining","first-page":"402","article-title":"Collaborative restricted Boltzmann machine for social event recommendation","author":"Jia","year":"2016"},{"key":"10.1016\/j.ins.2020.03.062_bib0033","series-title":"Proceedings of the 27th ACM International Conference on Information and Knowledge Management","first-page":"22","article-title":"Point-of-Interest recommendation: exploiting self-attentive autoencoders with neighbor-aware influence","author":"Ma","year":"2018"},{"key":"10.1016\/j.ins.2020.03.062_bib0034","series-title":"Proceedings of the 2015 IEEE International Conference on Acoustics, Speech and Signal Processing","first-page":"1996","article-title":"A novel approach for automatic acoustic novelty detection using a denoising autoencoder with bidirectional LSTM neural networks","author":"Marchi","year":"2015"},{"key":"10.1016\/j.ins.2020.03.062_bib0035","article-title":"Analysis of the click through rate of Chinese netizens through social software based on DeepFM algorithm","volume":"1284","author":"Li","year":"2019","journal-title":"J. Phys.: Conf. Ser."},{"key":"10.1016\/j.ins.2020.03.062_bib0036","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1016\/j.ins.2018.12.053","article-title":"GPS: factorized group preference-based similarity models for sparse sequential recommendation","volume":"481","author":"Yang","year":"2019","journal-title":"Inf. Sci."},{"key":"10.1016\/j.ins.2020.03.062_bib0037","series-title":"Proceedings of the 12th ACM\/IEEE-CS Joint Conference on Digital Libraries","first-page":"387","article-title":"Improving a hybrid literary book recommendation system through author ranking","author":"Vaz","year":"2012"},{"key":"10.1016\/j.ins.2020.03.062_bib0038","doi-asserted-by":"crossref","first-page":"1695","DOI":"10.1109\/ACCESS.2015.2481320","article-title":"Context-based collaborative filtering for citation recommendation","volume":"3","author":"Liu","year":"2015","journal-title":"IEEE Access"},{"key":"10.1016\/j.ins.2020.03.062_bib0039","series-title":"Proceedings of the 24th ACM International on Conference on Information and Knowledge Management","first-page":"1661","article-title":"Trirank: review-aware explainable recommendation by modeling aspects","author":"He","year":"2015"},{"key":"10.1016\/j.ins.2020.03.062_bib0040","series-title":"Proceedings of the 26th International Conference on World Wide Web","first-page":"1341","article-title":"A generic coordinate descent framework for learning from implicit feedback","author":"Bayer","year":"2017"},{"key":"10.1016\/j.ins.2020.03.062_bib0041","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.2020.03.062_bib0042","series-title":"Proceedings of the 24th International Conference on World Wide Web","first-page":"278","article-title":"A multi-view deep learning approach for cross domain user modeling in recommendation systems","author":"Elkahky","year":"2015"},{"key":"10.1016\/j.ins.2020.03.062_bib0043","series-title":"Proceedings of the2010 IEEE International Conference on Data Mining","first-page":"1025","article-title":"Generalized probabilistic matrix factorizations for collaborative filtering","author":"Shan","year":"2010"},{"key":"10.1016\/j.ins.2020.03.062_bib0044","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1017\/S0962492900002919","article-title":"Approximation theory of the MLP model in neural networks","volume":"8","author":"Pinkus","year":"1999","journal-title":"Acta Numer."}],"container-title":["Information Sciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/api.elsevier.com\/content\/article\/PII:S0020025520302425?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/api.elsevier.com\/content\/article\/PII:S0020025520302425?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T05:00:05Z","timestamp":1758085205000},"score":1,"resource":{"primary":{"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/linkinghub.elsevier.com\/retrieve\/pii\/S0020025520302425"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8]]},"references-count":44,"alternative-id":["S0020025520302425"],"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/j.ins.2020.03.062","relation":{},"ISSN":["0020-0255"],"issn-type":[{"value":"0020-0255","type":"print"}],"subject":[],"published":{"date-parts":[[2020,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A deep neural network of multi-form alliances for personalized recommendations","name":"articletitle","label":"Article Title"},{"value":"Information Sciences","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.1016\/j.ins.2020.03.062","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2020 Elsevier Inc. All rights reserved.","name":"copyright","label":"Copyright"}]}}