{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T04:28:15Z","timestamp":1773116895033,"version":"3.50.1"},"reference-count":39,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T00:00:00Z","timestamp":1745280000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T00:00:00Z","timestamp":1745280000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Complex Intell. Syst."],"published-print":{"date-parts":[[2025,6]]},"DOI":"10.1007\/s40747-025-01891-z","type":"journal-article","created":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T08:37:20Z","timestamp":1745311040000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Multi-objective recommendation system utilizing a multi-population knowledge migration framework"],"prefix":"10.1007","volume":"11","author":[{"given":"Liang","family":"Chu","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3487-5126","authenticated-orcid":false,"given":"Ye","family":"Tian","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,4,22]]},"reference":[{"key":"1891_CR1","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1016\/j.swevo.2013.08.003","volume":"14","author":"C Rana","year":"2014","unstructured":"Rana C, Jain SK (2014) An evolutionary clustering algorithm based on temporal features for dynamic recommender systems. Swarm Evol Comput 14:21\u201330","journal-title":"Swarm Evol Comput"},{"key":"1891_CR2","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1016\/j.swevo.2019.04.003","volume":"48","author":"L Pe\u0161ka","year":"2019","unstructured":"Pe\u0161ka L, Tashu TM, Horv\u00e1th T (2019) Swarm intelligence techniques in recommender systems\u2014a review of recent research. Swarm Evol Comput 48:201\u2013219","journal-title":"Swarm Evol Comput"},{"key":"1891_CR3","doi-asserted-by":"crossref","unstructured":"Chang S, Zhang Y, Tang J, Yin D, Chang Y, Hasegawa-Johnson MA, Huang TS (2017) Streaming recommender systems. In: Pro-ceedings of the 26th international conference on world wide web, International World Wide Web Conferences Steering Committee, Perth, Australia, pp 381\u2013389.","DOI":"10.1145\/3038912.3052627"},{"issue":"3","key":"1891_CR4","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1109\/MIC.2017.72","volume":"21","author":"B Smith","year":"2017","unstructured":"Smith B, Linden G (2017) Two decades of recommender systems at amazon.com. IEEE Internet Comput 21(3):12\u201318","journal-title":"IEEE Internet Comput"},{"key":"1891_CR5","unstructured":"Zheng Y (2018) Identifying dominators and followers in group decision making based on the personality traits. In: IUI workshops. Association for Computing Machinery, Tokyo Japan, pp 1\u20137"},{"key":"1891_CR6","doi-asserted-by":"crossref","unstructured":"Jambor T, Wang J (2010) Optimizing multiple objectives in collaborative filtering. In: Proceedings of the fourth ACM conference on recommender systems. Association for Computing Machinery, Barcelona, Spain, pp 55\u201362.","DOI":"10.1145\/1864708.1864723"},{"key":"1891_CR7","doi-asserted-by":"crossref","unstructured":"Park Y-J, Tuzhilin A (2008) The long tail of recommender systems and how to leverage it. In: Proceedings of the 2008 ACM conference on recommender systems. Association for Computing Machinery, Lausanne, Switzerland, pp 11\u201318","DOI":"10.1145\/1454008.1454012"},{"key":"1891_CR8","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1016\/j.knosys.2016.04.018","volume":"104","author":"S Wang","year":"2016","unstructured":"Wang S, Gong M, Li H, Yang J (2016) Multi-objective optimization for long tail recommendation. Knowl Based Syst 104:145\u2013155","journal-title":"Knowl Based Syst"},{"key":"1891_CR9","doi-asserted-by":"crossref","unstructured":"Jangid M, Kumar R (2024) Deep learning approaches to address cold start and long tail challenges in recommendation systems: a systematic review. Multimed Tools Appl 84:1\u201333","DOI":"10.1007\/s11042-024-20262-3"},{"key":"1891_CR10","doi-asserted-by":"crossref","unstructured":"Zhao Z, Zhou K, Wang X, Zhao WX, Pan F, Cao Z, Wen J-R (2023) Alleviating the long-tail problem in conversational recommender systems. In: Proceedings of the 17th ACM conference on recommender systems. Association for Computing Machinery, Singapore, pp 374\u2013385","DOI":"10.1145\/3604915.3608812"},{"key":"1891_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113648","volume":"159","author":"X Cai","year":"2020","unstructured":"Cai X, Hu Z, Zhao P, Zhang W, Chen J (2020) A hybrid recommendation system with many-objective evolutionary algorithm. Expert Syst Appl 159:113648","journal-title":"Expert Syst Appl"},{"key":"1891_CR12","doi-asserted-by":"crossref","unstructured":"Castells P, Hurley N, Vargas S (2021) Novelty and diversity in recommender systems. In: Recommender systems handbook. Springer, Berlin, pp 603\u2013646","DOI":"10.1007\/978-1-0716-2197-4_16"},{"key":"1891_CR13","doi-asserted-by":"publisher","first-page":"813","DOI":"10.1007\/s13042-017-0762-9","volume":"10","author":"T Silveira","year":"2019","unstructured":"Silveira T, Zhang M, Lin X, Liu Y, Ma S (2019) How good your recommender system is? A survey on evaluations in recommendation. Int J Mach Learn Cybern 10:813\u2013831","journal-title":"Int J Mach Learn Cybern"},{"key":"1891_CR14","doi-asserted-by":"crossref","unstructured":"Tian Y, Hu Y, Ma H, Wu L, Xingyi Z (2024) An evolutionary multitasking algorithm for efficient multiobjective recommendations. IEEE Trans Artif Intell 6:518\u2013532","DOI":"10.1109\/TAI.2024.3414289"},{"issue":"8","key":"1891_CR15","doi-asserted-by":"publisher","first-page":"8326","DOI":"10.1109\/TCYB.2021.3049712","volume":"52","author":"Z Wang","year":"2021","unstructured":"Wang Z, Zhen H-L, Deng J, Zhang Q, Li X, Yuan M, Zeng J (2021) Multiobjective optimization-aided decision-making system for large-scale manufacturing planning. IEEE Trans Cybern 52(8):8326\u20138339","journal-title":"IEEE Trans Cybern"},{"issue":"1","key":"1891_CR16","doi-asserted-by":"publisher","first-page":"483","DOI":"10.1109\/TCYB.2021.3126341","volume":"53","author":"Z Wang","year":"2021","unstructured":"Wang Z, Zhang Q, Ong Y-S, Yao S, Liu H, Luo J (2021) Choose appropriate subproblems for collaborative modeling in expensive multiobjective optimization. IEEE Trans Cybern 53(1):483\u2013496","journal-title":"IEEE Trans Cybern"},{"issue":"3","key":"1891_CR17","doi-asserted-by":"publisher","first-page":"1984","DOI":"10.1109\/TCYB.2023.3312476","volume":"54","author":"Z Wang","year":"2023","unstructured":"Wang Z, Yao S, Li G, Zhang Q (2023) Multiobjective combinatorial optimization using a single deep reinforcement learning model. IEEE Trans Cybern 54(3):1984\u20131996","journal-title":"IEEE Trans Cybern"},{"key":"1891_CR18","doi-asserted-by":"publisher","first-page":"234","DOI":"10.1016\/j.ins.2016.11.015","volume":"382","author":"T Di Noia","year":"2017","unstructured":"Di Noia T, Rosati J, Tomeo P, Di Sciascio E (2017) Adaptive multi-attribute diversity for recommender systems. Inf Sci 382:234\u2013253","journal-title":"Inf Sci"},{"issue":"1","key":"1891_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3457182","volume":"40","author":"S Patil","year":"2021","unstructured":"Patil S, Banerjee D, Sural S (2021) A graph theoretic approach for multi-objective budget constrained capsule wardrobe recommendation. ACM Trans Inf Syst (TOIS) 40(1):1\u201333","journal-title":"ACM Trans Inf Syst (TOIS)"},{"issue":"1","key":"1891_CR20","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1109\/MCI.2014.2369894","volume":"10","author":"Y Zuo","year":"2015","unstructured":"Zuo Y, Gong M, Zeng J, Ma L, Jiao L (2015) Personalized recommendation based on evolutionary multi-objective optimization [research frontier]. IEEE Comput Intell Mag 10(1):52\u201362","journal-title":"IEEE Comput Intell Mag"},{"key":"1891_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2019.112857","volume":"139","author":"A Jain","year":"2020","unstructured":"Jain A, Singh PK, Dhar J (2020) Multi-objective item evaluation for diverse as well as novel item recommendations. Expert Syst Appl 139:112857","journal-title":"Expert Syst Appl"},{"issue":"1","key":"1891_CR22","doi-asserted-by":"publisher","first-page":"1716352","DOI":"10.1155\/2018\/1716352","volume":"2018","author":"Q Lin","year":"2018","unstructured":"Lin Q, Wang X, Hu B, Ma L, Chen F, Li J, Coello Coello CA (2018) Multiobjective personalized recommendation algorithm using extreme point guided evolutionary computation. Complexity 2018(1):1716352","journal-title":"Complexity"},{"issue":"3","key":"1891_CR23","doi-asserted-by":"publisher","first-page":"589","DOI":"10.1109\/TCSS.2021.3055823","volume":"8","author":"G Wei","year":"2021","unstructured":"Wei G, Wu Q, Zhou M (2021) A hybrid probabilistic multiobjective evolutionary algorithm for commercial recommendation systems. IEEE Trans Comput Soc Syst 8(3):589\u2013598","journal-title":"IEEE Trans Comput Soc Syst"},{"key":"1891_CR24","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.125194","volume":"258","author":"S Sharma","year":"2024","unstructured":"Sharma S, Shakya HK (2024) Hybrid recommendation system for movies using artificial neural network. Expert Syst Appl 258:125194","journal-title":"Expert Syst Appl"},{"key":"1891_CR25","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1016\/j.swevo.2017.05.008","volume":"38","author":"J Chen","year":"2018","unstructured":"Chen J, Wang H, Yan Z et al (2018) Evolutionary heterogeneous clustering for rating prediction based on user collaborative filtering. Swarm Evol Comput 38:35\u201341","journal-title":"Swarm Evol Comput"},{"key":"1891_CR26","doi-asserted-by":"crossref","unstructured":"Herlocker JL, Konstan JA, Borchers A, Riedl J (1999) An algorithmic framework for performing collaborative filtering. In: Proceedings of the 22nd annual international ACM SIGIR conference on research and development in information retrieval. Association for Computing Machinery, Berkeley California, USA, pp 230\u2013237","DOI":"10.1145\/312624.312682"},{"key":"1891_CR27","doi-asserted-by":"crossref","unstructured":"Pazzani MJ (2007) Content-based recommendation systems. In:Peter B (ed) The Adaptive web: methods and strategies of web Personalization, 1st edn. Springer, Berlin, Heidelberg, pp 325\u2013341","DOI":"10.1007\/978-3-540-72079-9_10"},{"key":"1891_CR28","doi-asserted-by":"crossref","unstructured":"Sedhain S, Sanner S, Braziunas D, Xie L, Christensen J (2014) Social collaborative filtering for cold-start recommendations. In: Proceedings of the 8th ACM conference on recommender systems. Association for Computing Machinery, Foster City, Silicon Valley California USA, pp 345\u2013348","DOI":"10.1145\/2645710.2645772"},{"issue":"11","key":"1891_CR29","doi-asserted-by":"publisher","first-page":"992","DOI":"10.14778\/3402707.3402736","volume":"4","author":"Y Sun","year":"2011","unstructured":"Sun Y, Han J, Yan X, Yu PS, Wu T (2011) Pathsim: meta path-based top-k similarity search in heterogeneous information networks. Proc VLDB Endow 4(11):992\u20131003","journal-title":"Proc VLDB Endow"},{"issue":"22","key":"1891_CR30","doi-asserted-by":"publisher","first-page":"7004","DOI":"10.3923\/itj.2013.7004.7008","volume":"12","author":"Z Li","year":"2013","unstructured":"Li Z, Tao Q, Piqiang T (2013) Using key users of social networks to solve cold start problem in collaborative recommendation systems. Inf Technol J 12(22):7004","journal-title":"Inf Technol J"},{"issue":"5","key":"1891_CR31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3535101","volume":"55","author":"S Wu","year":"2022","unstructured":"Wu S, Sun F, Zhang W, Xie X, Cui B (2022) Graph neural networks in recommender systems: a survey. ACM Comput Surv 55(5):1\u201337","journal-title":"ACM Comput Surv"},{"key":"1891_CR32","doi-asserted-by":"crossref","unstructured":"Stergiopoulos V, Vassilakopoulos M, Tousidou E, Corral A (2024) An academic recommender system on large citation data based on clustering, graph modeling and deep learning. Knowl Inf Syst 66:1\u201334","DOI":"10.1007\/s10115-024-02094-7"},{"key":"1891_CR33","doi-asserted-by":"crossref","unstructured":"Wang X, He X, Wang M, Feng F, Chua T-S (2019) Neural graph collaborative filtering. In: Proceedings of the 42nd international ACM SIGIR conference on Research and development in information retrieval. Association for Computing Machinery, Paris, France, pp 165\u2013174","DOI":"10.1145\/3331184.3331267"},{"key":"1891_CR34","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. Association for Computing Machinery, Virtual Event, China, pp 639\u2013648","DOI":"10.1145\/3397271.3401063"},{"key":"1891_CR35","doi-asserted-by":"crossref","unstructured":"Carbonell J, Goldstein J (1998) The use of MMR, diversity-based reranking for reordering documents and producing summaries. In: Proceedings of the 21st annual international ACM SIGIR conference on research and development in information retrieval. Association for Computing Machinery, Melbourne, Australia, pp 335\u2013336","DOI":"10.1145\/290941.291025"},{"key":"1891_CR36","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1016\/j.eswa.2018.01.015","volume":"98","author":"NEI Karabadji","year":"2018","unstructured":"Karabadji NEI, Beldjoudi S, Seridi H, Aridhi S, Dhifli W (2018) Improving memory-based user collaborative filtering with evolutionary multi-objective optimization. Expert Syst Appl 98:153\u2013165","journal-title":"Expert Syst Appl"},{"key":"1891_CR37","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/j.jpdc.2016.10.014","volume":"103","author":"L Cui","year":"2017","unstructured":"Cui L, Ou P, Fu X, Wen Z, Lu N (2017) A novel multi-objective evolutionary algorithm for recommendation systems. J Parallel Distrib Comput 103:53\u201363","journal-title":"J Parallel Distrib Comput"},{"issue":"5","key":"1891_CR38","doi-asserted-by":"publisher","first-page":"1470","DOI":"10.1109\/TETCI.2022.3230942","volume":"7","author":"L Zhang","year":"2022","unstructured":"Zhang L, Zhang H, Liu S, Wang C, Zhao H (2022) A community division-based evolutionary algorithm for large-scale multi-objective recommendations. IEEE Trans Emerg Top Comput Intell 7(5):1470\u20131483","journal-title":"IEEE Trans Emerg Top Comput Intell"},{"key":"1891_CR39","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.ins.2021.07.077","volume":"579","author":"Z Cui","year":"2021","unstructured":"Cui Z, Zhao P, Hu Z, Cai X, Zhang W, Chen J (2021) An improved matrix factorization based model for many-objective optimization recommendation. Inf Sci 579:1\u201314","journal-title":"Inf Sci"}],"container-title":["Complex & Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-025-01891-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s40747-025-01891-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-025-01891-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,17]],"date-time":"2025-05-17T11:22:31Z","timestamp":1747480951000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s40747-025-01891-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,4,22]]},"references-count":39,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2025,6]]}},"alternative-id":["1891"],"URL":"https:\/\/doi.org\/10.1007\/s40747-025-01891-z","relation":{},"ISSN":["2199-4536","2198-6053"],"issn-type":[{"value":"2199-4536","type":"print"},{"value":"2198-6053","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,4,22]]},"assertion":[{"value":"24 January 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 March 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 April 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declaration"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"255"}}