{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T03:56:45Z","timestamp":1768535805588,"version":"3.49.0"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T00:00:00Z","timestamp":1714521600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T00:00:00Z","timestamp":1714521600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. & Cyber."],"published-print":{"date-parts":[[2024,10]]},"DOI":"10.1007\/s13042-024-02149-9","type":"journal-article","created":{"date-parts":[[2024,5,1]],"date-time":"2024-05-01T16:01:45Z","timestamp":1714579305000},"page":"4341-4356","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Towards platform profit-aware fairness in personalized recommendation"],"prefix":"10.1007","volume":"15","author":[{"given":"Shenghao","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiayang","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xianjun","family":"Deng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Heng","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenlu","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Laurence T.","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Celimuge","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,5,1]]},"reference":[{"issue":"3","key":"2149_CR1","doi-asserted-by":"publisher","first-page":"1056","DOI":"10.1109\/TNSE.2021.3100864","volume":"9","author":"S Liu","year":"2021","unstructured":"Liu S, Wang B, Yang L, Phili Y (2021) HNF: hybrid neural filtering based on centrality-aware random walk for personalized recommendation. IEEE Trans Netw Sci Eng 9(3):1056\u20131066","journal-title":"IEEE Trans Netw Sci Eng"},{"issue":"1","key":"2149_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3381016","volume":"4","author":"G Wang","year":"2020","unstructured":"Wang G, Zhang Y, Fang Z, Wang S, Zhang F, Zhang D (2020) FairCharge: a data-driven fairness-aware charging recommendation system for large-scale electric taxi fleets. Proc ACM Interact Mobile Wearable Ubiquit Technol 4(1):1\u201325","journal-title":"Proc ACM Interact Mobile Wearable Ubiquit Technol"},{"issue":"5","key":"2149_CR3","doi-asserted-by":"publisher","first-page":"3212","DOI":"10.1109\/TNSE.2021.3110677","volume":"9","author":"S Liu","year":"2021","unstructured":"Liu S, Wang B, Deng X, Yang L (2021) Self-attentive graph convolution network with latent group mining and collaborative filtering for personalized recommendation. IEEE Trans Netw Sci Eng 9(5):3212\u20133221","journal-title":"IEEE Trans Netw Sci Eng"},{"key":"2149_CR4","doi-asserted-by":"crossref","unstructured":"Zhang Y, Zhao Q, Zhang Y, Friedman D, Zhang M, Liu Y, Ma S (2016) Economic recommendation with surplus maximization. In: Proceedings of the 25th International Conference on world wide web pp 73\u201383","DOI":"10.1145\/2872427.2882973"},{"key":"2149_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.elerap.2022.101195","volume":"55","author":"N Ghanem","year":"2022","unstructured":"Ghanem N, Leitner S, Jannach D (2022) Balancing consumer and business value of recommender systems: a simulation-based analysis. Electron Commer Res Appl 55:101195","journal-title":"Electron Commer Res Appl"},{"key":"2149_CR6","doi-asserted-by":"crossref","unstructured":"Naghiaei M, Rahmani H, Deldjoo Y (2022) CPFair: personalized consumer and producer fairness re-ranking for recommender systems. In: Proceedings of the 45th International ACM SIGIR Conference on research and development in information retrieval, pp 770\u2013779","DOI":"10.1145\/3477495.3531959"},{"issue":"4","key":"2149_CR7","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1109\/MIS.2020.3007207","volume":"35","author":"K Zhao","year":"2020","unstructured":"Zhao K, Xi W, Wang Z, Zhao J, Wang R, Jiang Z (2020) SMSS: secure member selection strategy in federated learning. IEEE Intell Syst 35(4):37\u201349","journal-title":"IEEE Intell Syst"},{"key":"2149_CR8","doi-asserted-by":"crossref","unstructured":"Wu H, Mitra B, Ma C, Diaz F, Liu X (2022) Joint multisided exposure fairness for recommendation. In: Proceedings of the 45th International ACM SIGIR Conference on research and development in information retrieval, pp 703\u2013714","DOI":"10.1145\/3477495.3532007"},{"issue":"10","key":"2149_CR9","doi-asserted-by":"publisher","first-page":"983","DOI":"10.1001\/jama.2019.0554","volume":"321","author":"M Mueller","year":"2019","unstructured":"...Mueller M, Van R, Meybohm P, Aranko K, Aubron C, Burger R, Carson JL, Cichutek K, De Buck E, Devine D, Fergusson D, Foll\u00e9a G, French C, Frey KP, Gammon R, Levy JH, Murphy MF, Ozier Y, Pavenski K, So-Osman C, Tiberghien P, Volmink J, Waters JH, Wood EM, Seifried E (2019) Patient blood management: recommendations from the 2018 Frankfurt Consensus Conference. JAMA 321(10):983\u2013997","journal-title":"JAMA"},{"key":"2149_CR10","doi-asserted-by":"crossref","unstructured":"Wu Y, Xie R, Zhu Y, Zhuang F, Xiang A, Zhang X, Lin L, He Q (2022) Selective fairness in recommendation via prompts. In: Proceedings of the 45th International ACM SIGIR Conference on research and development in information retrieval, pp 2657\u20132662","DOI":"10.1145\/3477495.3531913"},{"key":"2149_CR11","doi-asserted-by":"crossref","unstructured":"Rahmani H, Naghiaei M, Dehghan M, Aliannejadi M (2022) Experiments on generalizability of user-oriented fairness in recommender systems. In: Proceedings of the 45th International ACM SIGIR Conference on research and development in information retrieval, pp 2755\u20132764","DOI":"10.1145\/3477495.3531718"},{"key":"2149_CR12","doi-asserted-by":"crossref","unstructured":"Borges R, Stefanidis K (2022) F2VAE: a framework for mitigating user unfairness in recommendation systems. In: Proceedings of the 37th ACM\/SIGAPP Symposium on applied computing, pp 1391-1398","DOI":"10.1145\/3477314.3507152"},{"issue":"12","key":"2149_CR13","doi-asserted-by":"publisher","first-page":"2850","DOI":"10.1109\/TMC.2019.2934445","volume":"19","author":"J Yu","year":"2019","unstructured":"Yu J, Liu J, Zhang R, Chen L, Gong W, Zhang S (2019) Multi-seed group labeling in RFID systems. IEEE Trans Mob Comput 19(12):2850\u20132862","journal-title":"IEEE Trans Mob Comput"},{"issue":"20","key":"2149_CR14","doi-asserted-by":"publisher","first-page":"18097","DOI":"10.1007\/s00521-022-07373-4","volume":"34","author":"H Liu","year":"2022","unstructured":"Liu H, Wang Y, Lin H, Xu B, Zhao N (2022) Mitigating sensitive data exposure with adversarial learning for fairness recommendation systems. Neural Comput Appl 34(20):18097\u201318111","journal-title":"Neural Comput Appl"},{"key":"2149_CR15","doi-asserted-by":"crossref","unstructured":"Xu C, Chen S, Xu J, Shen W, Zhang X, Wang G, Dong Z (2023) P-MMF: provider max-min fairness re-ranking in recommender system. In: Proceedings of the ACM Web Conference 2023, pp 3701\u20133711","DOI":"10.1145\/3543507.3583296"},{"key":"2149_CR16","doi-asserted-by":"crossref","unstructured":"Marras M, Boratto L, Ramos G, Fenu G (2022) Regulating group exposure for item providers in recommendation. In: Proceedings of the 45th International ACM SIGIR Conference on research and development in information retrieval, pp 1839\u20131843","DOI":"10.1145\/3477495.3531760"},{"issue":"1","key":"2149_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3495163","volume":"13","author":"C Li","year":"2022","unstructured":"Li C, Hsu C, Zhang Y (2022) Fairsr: fairness-aware sequential recommendation through multi-task learning with preference graph embeddings. ACM Trans Intell Syst Technol (TIST) 13(1):1\u201321","journal-title":"ACM Trans Intell Syst Technol (TIST)"},{"key":"2149_CR18","doi-asserted-by":"crossref","unstructured":"Patro G, Chakraborty A, Ganguly N, Gummadi K (2020) Incremental fairness in two-sided market platforms: on smoothly updating recommendations. In: Proceedings of the AAAI Conference on artificial intelligence, pp 181\u2013188","DOI":"10.1609\/aaai.v34i01.5349"},{"key":"2149_CR19","doi-asserted-by":"crossref","unstructured":"Liu Q, Wu Y, Liu Q (2022) Multifactor recommendation-based video caching strategy in mobile edge computing. In: 2022 IEEE 21st International Conference on ubiquitous computing and communications (IUCC\/CIT\/DSCI\/SmartCNS), pp 81\u201390","DOI":"10.1109\/IUCC-CIT-DSCI-SmartCNS57392.2022.00026"},{"issue":"1","key":"2149_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3586993","volume":"42","author":"Y Wu","year":"2023","unstructured":"Wu Y, Cao J, Xu G (2023) FASTER: a dynamic fairness-assurance strategy for session-based recommender systems. ACM Trans Inform Syst 42(1):1\u201326","journal-title":"ACM Trans Inform Syst"},{"key":"2149_CR21","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1007\/s00607-018-0687-5","volume":"102","author":"D Kotkov","year":"2020","unstructured":"Kotkov D, Veijalainen J, Wang S (2020) How does serendipity affect diversity in recommender systems? A serendipity-oriented greedy algorithm. Computing 102:393\u2013411","journal-title":"Computing"},{"key":"2149_CR22","doi-asserted-by":"publisher","first-page":"807","DOI":"10.1007\/s11042-021-11300-5","volume":"81","author":"R Katarya","year":"2022","unstructured":"Katarya R, Saini R (2022) Enhancing the wine tasting experience using greedy clustering wine recommender system. Multimedia Tools Appl 81:807\u2013840","journal-title":"Multimedia Tools Appl"},{"key":"2149_CR23","unstructured":"Elizabeth G, Zhang C, Ludovico B, Maria S, Mirko M (2021) The winner takes it all: geographic imbalance and provider (un) fairness in educational recommender systems. In: Proceedings of the 44th International ACM SIGIR Conference on research and development in information retrieval, pp 1808\u20131812"},{"key":"2149_CR24","doi-asserted-by":"crossref","unstructured":"Kaya M, Bridge D, Tintarev N (2020) Ensuring fairness in group recommendations by rank-sensitive balancing of relevance. In: Proceedings of the 14th ACM Conference on recommender systems, pp 101\u2013110","DOI":"10.1145\/3383313.3412232"},{"key":"2149_CR25","doi-asserted-by":"crossref","unstructured":"Zhao C, Wu L, Shao P, Zhang K, Hong R, Wang M (2023) Fair representation learning for recommendation: a mutual information perspective. In: Proceedings of the AAAI Conference on artificial intelligence, pp 4911\u20134919","DOI":"10.1609\/aaai.v37i4.25617"},{"key":"2149_CR26","doi-asserted-by":"crossref","unstructured":"Jiang L, Wang S, Guo B, et al (2023) FairCod: a fairness-aware concurrent dispatch system for large-scale instant delivery services. In: Proceedings of the 29th ACM SIGKDD Conference on knowledge discovery and data mining, pp 4229\u20134238","DOI":"10.1145\/3580305.3599824"},{"issue":"5","key":"2149_CR27","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3610302","volume":"14","author":"Y Li","year":"2023","unstructured":"Li Y, Chen H, Xu S, Ge Y, Tan J, Liu S, Zhang Y (2023) Fairness in recommendation: foundations, methods, and applications. ACM Trans Intell Syst Technol 14(5):1\u201348","journal-title":"ACM Trans Intell Syst Technol"},{"key":"2149_CR28","doi-asserted-by":"crossref","unstructured":"Marcher M, Christensen I, Grabarczyk P, Graversen T, Brabrand C (2021) Computing educational activities involving people rather than things appeal more to women (Recruitment Perspective). In: Proceedings of the 17th ACM Conference on international computing education research, pp 127\u2013144","DOI":"10.1145\/3446871.3469758"},{"key":"2149_CR29","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1007\/s00778-021-00697-y","volume":"31","author":"E Pitoura","year":"2022","unstructured":"Pitoura E, Stefanidis K, Koutrika G (2022) Fairness in rankings and recommendations: an overview. VLDB J 31:431\u2013458","journal-title":"VLDB J"},{"key":"2149_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.121164","volume":"236","author":"R Lopes","year":"2024","unstructured":"Lopes R, Alves R, Ledent A, Santos R, Kloft M (2024) Recommendations with minimum exposure guarantees: a post-processing framework. Expert Syst Appl 236:121164","journal-title":"Expert Syst Appl"},{"key":"2149_CR31","doi-asserted-by":"crossref","unstructured":"Islam R, Keya K, Zeng Z, Pan S, Foulds J (2021) Debiasing career recommendations with neural fair collaborative filtering. In: Proceedings of the Web Conference 2021, pp 3779\u20133790","DOI":"10.1145\/3442381.3449904"},{"key":"2149_CR32","doi-asserted-by":"crossref","unstructured":"Wu C, Wu F, Wang X, Huang Y, Xie X (2021) Fairness-aware news recommendation with decomposed adversarial learning. In: Proceedings of the AAAI Conference on artificial intelligence 35(5):4462\u20134469","DOI":"10.1609\/aaai.v35i5.16573"},{"issue":"2","key":"2149_CR33","first-page":"1","volume":"41","author":"H Wu","year":"2022","unstructured":"Wu H, Ma C, Mitra B, Diaz F, Liu X (2022) A multi-objective optimization framework for multi-stakeholder fairness-aware recommendation. ACM Trans Inform Syst 41(2):1\u201329","journal-title":"ACM Trans Inform Syst"},{"key":"2149_CR34","doi-asserted-by":"crossref","unstructured":"He R, Mcauley J (2016) VBPR: visual Bayesian personalized ranking from implicit feedback. In: Proceedings of the AAAI Conference on artificial intelligence, pp 144\u2013150","DOI":"10.1609\/aaai.v30i1.9973"},{"key":"2149_CR35","doi-asserted-by":"crossref","unstructured":"Liang D, Krishnan R, Hoffman M, Jebara T (2018) Variational autoencoders for collaborative filtering. In: Proceedings of the 2018 World Wide Web Conference, pp 689\u2013698","DOI":"10.1145\/3178876.3186150"},{"key":"2149_CR36","unstructured":"Gopalan P, Hofman J, Blei D (2015) Scalable recommendation with hierarchical poisson factorization. In: Proceedings of the Thirty-First Conference on uncertainty in artificial intelligence, pp 144\u2013150"},{"key":"2149_CR37","doi-asserted-by":"crossref","unstructured":"He X, Deng K, Wang X, Li Y, Zhang Y, Wang M (2020) LightGCN: simplifying and powering graph convolution network for recommendation. In: Proceedings of the 43rd International ACM SIGIR Conference on research and development in information retrieval, pp 639\u2013648","DOI":"10.1145\/3397271.3401063"},{"issue":"3","key":"2149_CR38","doi-asserted-by":"publisher","first-page":"644","DOI":"10.1137\/0113043","volume":"13","author":"WF Tyndall","year":"1965","unstructured":"Tyndall WF (1965) A duality theorem for a class of continuous linear programming problems. J Soc Ind Appl Math 13(3):644\u2013666","journal-title":"J Soc Ind Appl Math"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-024-02149-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-024-02149-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-024-02149-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,13]],"date-time":"2024-09-13T16:35:16Z","timestamp":1726245316000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-024-02149-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,1]]},"references-count":38,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2024,10]]}},"alternative-id":["2149"],"URL":"https:\/\/doi.org\/10.1007\/s13042-024-02149-9","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,5,1]]},"assertion":[{"value":"8 January 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 March 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 May 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}