{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T18:39:46Z","timestamp":1784918386187,"version":"3.55.0"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2022,2,8]],"date-time":"2022-02-08T00:00:00Z","timestamp":1644278400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,2,8]],"date-time":"2022-02-08T00:00:00Z","timestamp":1644278400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100012165","name":"Key Technologies Research and Development Program","doi-asserted-by":"publisher","award":["2020YFB1005804"],"award-info":[{"award-number":["2020YFB1005804"]}],"id":[{"id":"10.13039\/501100012165","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61632009"],"award-info":[{"award-number":["61632009"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2017A030308006"],"award-info":[{"award-number":["2017A030308006"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Ambient Intell Human Comput"],"published-print":{"date-parts":[[2023,8]]},"DOI":"10.1007\/s12652-022-03709-z","type":"journal-article","created":{"date-parts":[[2022,2,8]],"date-time":"2022-02-08T04:46:06Z","timestamp":1644295566000},"page":"10555-10565","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":39,"title":["Personalized federated recommendation system with historical parameter clustering"],"prefix":"10.1007","volume":"14","author":[{"given":"Zhiyong","family":"Jie","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6120-6358","authenticated-orcid":false,"given":"Shuhong","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junqiu","family":"Lai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad","family":"Arif","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zongyuan","family":"He","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,2,8]]},"reference":[{"issue":"6","key":"3709_CR1","doi-asserted-by":"publisher","first-page":"734","DOI":"10.1109\/TKDE.2005.99","volume":"17","author":"G Adomavicius","year":"2005","unstructured":"Adomavicius G, Tuzhilin A (2005) Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Transact Knowl Data Eng 17(6):734\u2013749. https:\/\/doi.org\/10.1109\/TKDE.2005.99","journal-title":"IEEE Transact Knowl Data Eng"},{"key":"3709_CR2","unstructured":"Ammad-ud-din M, Ivannikova E, Khan SA, Oyomno W, Fu Q, Tan KE, Flanagan A (2019) Federated collaborative filtering for privacy-preserving personalized recommendation system. CoRR abs\/1901.09888, arXiv:1901.09888"},{"key":"3709_CR3","doi-asserted-by":"publisher","unstructured":"Anelli VW, Deldjoo Y, Noia TD, Ferrara A, Narducci F (2021) Federank: user controlled feedback with federated recommender systems. In: Hiemstra D, Moens M, Mothe J, Perego R, Potthast M, Sebastiani F (eds) Advances in information retrieval - 43rd European Conference on IR Research, ECIR 2021, Virtual Event, March 28 - April 1, 2021, Proceedings, Part I, Springer, Lecture Notes in Computer Science, vol 12656, pp 32\u201347, https:\/\/doi.org\/10.1007\/978-3-030-72113-8_3","DOI":"10.1007\/978-3-030-72113-8_3"},{"key":"3709_CR4","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1145\/245108.245124","volume":"40","author":"M Balabanovic","year":"1997","unstructured":"Balabanovic M, Shoham Y (1997) Fab: content-based, collaborative recommendation. Commun ACM 40:66\u201372","journal-title":"Commun ACM"},{"key":"3709_CR5","unstructured":"Basu C, Hirsh H, Cohen W (1998) Recommendation as classification: using social and content-based information in recommendation. In: In Proceedings of the Fifteenth National Conference on Artificial Intelligence, AAAI Press, pp 714\u2013720"},{"key":"3709_CR6","unstructured":"Billsus D, Pazzani MJ (1998) Learning collaborative information filters. In: In Proc. 15th International Conf. on Machine Learning, Morgan Kaufmann, pp 46\u201354"},{"key":"3709_CR7","unstructured":"Bonawitz KA, Eichner H, Grieskamp W, Huba D, Ingerman A, Ivanov V, Kiddon C, Kone\u010dn\u00fd J, Mazzocchi S, McMahan B, Overveldt TV, Petrou D, Ramage D, Roselander J (2019) Towards federated learning at scale: system design. In: Talwalkar A, Smith V, Zaharia M (eds) Proceedings of machine learning and systems 2019, MLSys 2019, Stanford, CA, USA, March 31 - April 2, 2019, mlsys.org"},{"key":"3709_CR8","unstructured":"Brendan McMahan H, Moore E, Ramage D, Hampson S, Ag\u00fcera y Arcas B (2016) Communication-efficient learning of deep networks from decentralized data. arXiv e-prints arXiv:1602.05629"},{"issue":"5","key":"3709_CR9","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1109\/MIS.2020.3014880","volume":"36","author":"D Chai","year":"2021","unstructured":"Chai D, Wang L, Chen K, Yang Q (2021) Secure federated matrix factorization. IEEE Intell Syst 36(5):11\u201320. https:\/\/doi.org\/10.1109\/MIS.2020.3014880","journal-title":"IEEE Intell Syst"},{"issue":"10","key":"3709_CR10","doi-asserted-by":"publisher","first-page":"9266","DOI":"10.1109\/JIOT.2020.2995162","volume":"7","author":"TC Chiu","year":"2020","unstructured":"Chiu TC, Shih YY, Pang AC, Wang CS, Weng W, Chou CT (2020) Semisupervised distributed learning with non-iid data for aiot service platform. IEEE Internet Things J 7(10):9266\u20139277. https:\/\/doi.org\/10.1109\/JIOT.2020.2995162","journal-title":"IEEE Internet Things J"},{"key":"3709_CR11","first-page":"1","volume-title":"Knowledge and systems sciences","author":"DT Dinh","year":"2019","unstructured":"Dinh DT, Fujinami T, Huynh VN (2019) Estimating the optimal number of clusters in categorical data clustering by silhouette coefficient. In: Chen J, Huynh VN, Nguyen GN, Tang X (eds) Knowledge and systems sciences. Springer Singapore, Singapore, pp 1\u201317"},{"key":"3709_CR12","doi-asserted-by":"publisher","first-page":"418","DOI":"10.1016\/j.ins.2021.04.076","volume":"571","author":"DT Dinh","year":"2021","unstructured":"Dinh DT, Huynh VN, Sriboonchitta S (2021) Clustering mixed numerical and categorical data with missing values. Inform Sci 571:418\u2013442. https:\/\/doi.org\/10.1016\/j.ins.2021.04.076","journal-title":"Inform Sci"},{"issue":"12","key":"3709_CR13","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1145\/138859.138867","volume":"35","author":"D Goldberg","year":"1992","unstructured":"Goldberg D, Nichols D, Oki BM, Terry D (1992) Using collaborative filtering to weave an information tapestry. Commun ACM 35(12):61\u201370. https:\/\/doi.org\/10.1145\/138859.138867","journal-title":"Commun ACM"},{"key":"3709_CR14","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1016\/j.inffus.2021.01.008","volume":"71","author":"A Holzinger","year":"2021","unstructured":"Holzinger A, Malle B, Saranti A, Pfeifer B (2021) Towards multi-modal causability with graph neural networks enabling information fusion for explainable ai. Inform Fusion 71:28\u201337. https:\/\/doi.org\/10.1016\/j.inffus.2021.01.008","journal-title":"Inform Fusion"},{"issue":"007","key":"3709_CR15","first-page":"1619","volume":"041","author":"L Huang","year":"2018","unstructured":"Huang L, Jiang B, Lv S, Liu Y, Li D (2018) Review of recommendation system based on deep learning. J Comput Sci 041(007):1619\u20131647","journal-title":"J Comput Sci"},{"key":"3709_CR16","doi-asserted-by":"crossref","unstructured":"Huang Y, Chu L, Zhou Z, Wang L, Liu J, Pei J, Zhang Y (2021) Personalized cross-silo federated learning on non-iid data. In: Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021, AAAI Press, pp 7865\u20137873, https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/view\/16960","DOI":"10.1609\/aaai.v35i9.16960"},{"key":"3709_CR17","first-page":"1","volume":"179","author":"J Karlgren","year":"1990","unstructured":"Karlgren J (1990) An algebra for recommendations: using reader data as a basis for measuring document proximity. SYSLAB Tech Rep 179:1-11","journal-title":"SYSLAB Tech Rep"},{"key":"3709_CR18","unstructured":"Kone\u010dn\u00fd J, McMahan HB, Yu FX, Richt\u00e1rik P, Suresh AT, Bacon D (2016) Federated learning: strategies for improving communication efficiency. CoRR abs\/1610.05492, arXiv:1610.05492"},{"issue":"8","key":"3709_CR19","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1109\/MC.2009.263","volume":"42","author":"Y Koren","year":"2009","unstructured":"Koren Y, Bell R, Volinsky C (2009) Matrix factorization techniques for recommender systems. Computer 42(8):30\u201337. https:\/\/doi.org\/10.1109\/MC.2009.263","journal-title":"Computer"},{"issue":"3","key":"3709_CR20","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1109\/MSP.2020.2975749","volume":"37","author":"T Li","year":"2020","unstructured":"Li T, Sahu AK, Talwalkar A, Smith V (2020a) Federated learning: challenges, methods, and future directions. IEEE Signal Proces Mag 37(3):50\u201360. https:\/\/doi.org\/10.1109\/MSP.2020.2975749","journal-title":"IEEE Signal Proces Mag"},{"key":"3709_CR21","unstructured":"Li T, Sahu AK, Zaheer M, Sanjabi M, Talwalkar A, Smith V (2020b) Federated optimization in heterogeneous networks. In: Dhillon I, Papailiopoulos D, Sze V (eds) Proceedings of Machine Learning and Systems, pp 429\u2013450"},{"key":"3709_CR22","unstructured":"McMahan B, Moore E, Ramage D, Hampson S, y\u00a0Arcas BA (2017) Communication-efficient learning of deep networks from decentralized data. In: Singh A, Zhu XJ (eds) Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, AISTATS 2017, 20-22 April 2017, Fort Lauderdale, FL, USA, PMLR, Proceedings of Machine Learning Research, vol\u00a054, pp 1273\u20131282"},{"key":"3709_CR23","unstructured":"Naumov M, Mudigere D, Shi HJM, Huang J, Sundaraman N, Park J, Wang X, Gupta U, Wu CJ, Azzolini AG, Dzhulgakov D, Mallevich A, Cherniavskii I, Lu Y, Krishnamoorthi R, Yu A, Kondratenko V, Pereira S, Chen X, Chen W, Rao V, Jia B, Xiong L, Smelyanskiy M (2019) Deep learning recommendation model for personalization and recommendation systems. arXiv e-prints arXiv:1906.00091"},{"key":"3709_CR24","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1007\/978-3-540-72079-9_10","volume-title":"The adaptive web: methods and strategies of web personalization. Volume 4321 of lecture notes in computer science","author":"MJ Pazzani","year":"2007","unstructured":"Pazzani MJ, Billsus D (2007) Content-based recommendation systems. The adaptive web: methods and strategies of web personalization. Volume 4321 of lecture notes in computer science. Springer-Verlag, Berlin, pp 325\u2013341"},{"key":"3709_CR25","doi-asserted-by":"crossref","unstructured":"Qi T, Wu F, Wu C, Huang Y, Xie X (2020) Privacy-preserving news recommendation model training via federated learning. CoRR abs\/2003.09592, arXiv:2003.09592","DOI":"10.18653\/v1\/2020.findings-emnlp.128"},{"key":"3709_CR26","doi-asserted-by":"publisher","unstructured":"Resnick P, Iacovou N, Suchak M, Bergstrom P, Riedl J (1994) Grouplens: An open architecture for collaborative filtering of netnews. In: Proceedings of the 1994 ACM Conference on Computer Supported Cooperative Work, Association for Computing Machinery, New York, NY, USA, CSCW \u201994, p 175-186, https:\/\/doi.org\/10.1145\/192844.192905","DOI":"10.1145\/192844.192905"},{"key":"3709_CR27","doi-asserted-by":"publisher","unstructured":"Sarwar B, Karypis G, Konstan J, Riedl J (2001) Item-based collaborative filtering recommendation algorithms. In: Proceedings of the 10th International Conference on World Wide Web, Association for Computing Machinery, New York, NY, USA, WWW \u201901, p 285-295, https:\/\/doi.org\/10.1145\/371920.372071","DOI":"10.1145\/371920.372071"},{"key":"3709_CR28","doi-asserted-by":"publisher","DOI":"10.1155\/2009\/421425","author":"X Su","year":"2009","unstructured":"Su X, Khoshgoftaar TM (2009) A survey of collaborative filtering techniques. Adv in Artif Intell. https:\/\/doi.org\/10.1155\/2009\/421425","journal-title":"Adv in Artif Intell"},{"issue":"002","key":"3709_CR29","doi-asserted-by":"publisher","first-page":"350","DOI":"10.3724\/SP.J.1001.2009.00350","volume":"20","author":"H Xu","year":"2009","unstructured":"Xu H, Wu X, Li X, Yan B (2009) A comparative study of internet recommendation systems. J Softw 20(002):350\u2013362","journal-title":"J Softw"},{"key":"3709_CR30","doi-asserted-by":"publisher","DOI":"10.1145\/3298981","author":"Q Yang","year":"2019","unstructured":"Yang Q, Liu Y, Chen T, Tong Y (2019) Federated machine learning: concept and applications. ACM Trans Intell Syst Technol. https:\/\/doi.org\/10.1145\/3298981","journal-title":"ACM Trans Intell Syst Technol"},{"key":"3709_CR31","doi-asserted-by":"crossref","unstructured":"Yi J, Wu F, Wu C, Liu R, Sun G, Xie X (2021) Efficient-fedrec: Efficient federated learning framework for privacy-preserving news recommendation. In: Moens M, Huang X, Specia L, Yih SW (eds) Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, EMNLP 2021, Virtual Event \/ Punta Cana, Dominican Republic, 7-11 November, 2021, Association for Computational Linguistics, pp 2814\u20132824","DOI":"10.18653\/v1\/2021.emnlp-main.223"},{"key":"3709_CR32","doi-asserted-by":"publisher","DOI":"10.1145\/3285029","author":"S Zhang","year":"2019","unstructured":"Zhang S, Yao L, Sun A, Tay Y (2019) Deep learning based recommender system: a survey and new perspectives. ACM Comput Surv. https:\/\/doi.org\/10.1145\/3285029","journal-title":"ACM Comput Surv"},{"key":"3709_CR33","unstructured":"Zhao Y, Li M, Lai L, Suda N, Civin D, Chandra V (2018) Federated learning with non-iid data. CoRR abs\/1806.00582, arxiv:1806.00582"}],"container-title":["Journal of Ambient Intelligence and Humanized Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-022-03709-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12652-022-03709-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-022-03709-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,21]],"date-time":"2023-06-21T15:15:26Z","timestamp":1687360526000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12652-022-03709-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,8]]},"references-count":33,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2023,8]]}},"alternative-id":["3709"],"URL":"https:\/\/doi.org\/10.1007\/s12652-022-03709-z","relation":{},"ISSN":["1868-5137","1868-5145"],"issn-type":[{"value":"1868-5137","type":"print"},{"value":"1868-5145","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,8]]},"assertion":[{"value":"5 August 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 January 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 February 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}