{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T14:56:04Z","timestamp":1778079364984,"version":"3.51.4"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T00:00:00Z","timestamp":1711929600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,4,1]],"date-time":"2024-04-01T00:00:00Z","timestamp":1711929600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12371515"],"award-info":[{"award-number":["12371515"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62176225"],"award-info":[{"award-number":["62176225"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62171391"],"award-info":[{"award-number":["62171391"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2024,4]]},"DOI":"10.1007\/s10489-024-05426-w","type":"journal-article","created":{"date-parts":[[2024,4,17]],"date-time":"2024-04-17T11:02:50Z","timestamp":1713351770000},"page":"5216-5234","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["CA-PDBPR: category-aware privacy preserving POI recommendation using decentralized Bayesian personalized ranking"],"prefix":"10.1007","volume":"54","author":[{"given":"Qinyun","family":"Gao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shenbao","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5805-072X","authenticated-orcid":false,"given":"Bilian","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Langcai","family":"Cao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,4,17]]},"reference":[{"key":"5426_CR1","first-page":"2016","volume":"679","author":"P Regulation","year":"2016","unstructured":"Regulation P (2016) Regulation (eu) 2016\/679 of the european parliament and of the council. Regulation (eu) 679:2016","journal-title":"Regulation (eu)"},{"key":"5426_CR2","doi-asserted-by":"crossref","unstructured":"Parameswaran R, Blough DM (2007) Privacy preserving collaborative filtering using data obfuscation. In: 2007 IEEE International Conference on Granular Computing (GRC 2007), pp. 380\u2013380. IEEE","DOI":"10.1109\/GRC.2007.4403128"},{"issue":"5","key":"5426_CR3","doi-asserted-by":"publisher","first-page":"5033","DOI":"10.1016\/j.eswa.2011.11.037","volume":"39","author":"S Berkovsky","year":"2012","unstructured":"Berkovsky S, Kuflik T, Ricci F (2012) The impact of data obfuscation on the accuracy of collaborative filtering. Expert Syst Appl 39(5):5033\u20135042","journal-title":"Expert Syst Appl"},{"key":"5426_CR4","doi-asserted-by":"crossref","unstructured":"Luo Z, Chen S, Li Y (2013) A distributed anonymization scheme for privacy preserving recommendation systems. In: 2013 IEEE 4th International Conference on Software Engineering and Service Science, pp. 491\u2013494. IEEE","DOI":"10.1109\/ICSESS.2013.6615356"},{"key":"5426_CR5","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1016\/j.pmcj.2017.03.008","volume":"41","author":"JE Rubio","year":"2017","unstructured":"Rubio JE, Alcaraz C, Lopez J (2017) Recommender system for privacy preserving solutions in smart metering. Pervasive Mob Comput 41:205\u2013218","journal-title":"Pervasive Mob Comput"},{"issue":"3","key":"5426_CR6","doi-asserted-by":"publisher","first-page":"1053","DOI":"10.1109\/TIFS.2012.2190726","volume":"7","author":"Z Erkin","year":"2012","unstructured":"Erkin Z, Veugen T, Toft T, Lagendijk RL (2012) Generating private recommendations efficiently using homomorphic encryption and data packing. IEEE Trans Inf Forensics Secur 7(3):1053\u20131066","journal-title":"IEEE Trans Inf Forensics Secur"},{"key":"5426_CR7","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1016\/j.ins.2020.07.046","volume":"543","author":"Y Huo","year":"2021","unstructured":"Huo Y, Chen B, Tang J, Zeng Y (2021) Privacy-preserving point-of-interest recommendation based on geographical and social influence. Inf Sci 543:202\u2013218","journal-title":"Inf Sci"},{"key":"5426_CR8","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1016\/j.neucom.2022.01.079","volume":"483","author":"X Ran","year":"2022","unstructured":"Ran X, Wang Y, Zhang LY, Ma J (2022) A differentially private matrix factorization based on vector perturbation for recommender system. Neurocomputing 483:32\u201341","journal-title":"Neurocomputing"},{"key":"5426_CR9","unstructured":"Kone\u010dn\u1ef3 J, McMahan HB, Yu FX, Richt\u00e1rik P, Suresh AT, Bacon D (2016) Federated learning: Strategies for improving communication efficiency. arXiv:1610.05492"},{"issue":"5","key":"5426_CR10","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1109\/MIS.2020.3017205","volume":"36","author":"G Lin","year":"2020","unstructured":"Lin G, Liang F, Pan W, Ming Z (2020) Fedrec: Federated recommendation with explicit feedback. IEEE Intell Syst 36(5):21\u201330","journal-title":"IEEE Intell Syst"},{"key":"5426_CR11","doi-asserted-by":"crossref","unstructured":"Zhu Z, Si S, Wang J, Xiao J (2022) Cali3f: Calibrated fast fair federated recommendation system. In: 2022 International Joint Conference on Neura Networks (IJCNN), pp. 1\u20138. IEEE","DOI":"10.1109\/IJCNN55064.2022.9892624"},{"key":"5426_CR12","doi-asserted-by":"crossref","unstructured":"Lin Z, Pan W, Ming Z (2021) Fr-fmss: Federated recommendation via fake marks and secret sharing. In: Proceedings of the 15th ACM Conference on Recommender Systems, pp. 668\u2013673","DOI":"10.1145\/3460231.3478855"},{"key":"5426_CR13","doi-asserted-by":"crossref","unstructured":"Yuan W, Yin H, Wu F, Zhang S, He T, Wang H (2023) Federated unlearning for on-device recommendation. In: Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, pp. 393\u2013401","DOI":"10.1145\/3539597.3570463"},{"key":"5426_CR14","doi-asserted-by":"crossref","unstructured":"Yuan W, Yang C, Nguyen QVH, Cui L, He T, Yin H (2023) Interaction level membership inference attack against federated recommender systems. arXiv:2301.10964","DOI":"10.1145\/3543507.3583359"},{"issue":"3","key":"5426_CR15","doi-asserted-by":"publisher","first-page":"3563","DOI":"10.1007\/s10489-022-03578-1","volume":"53","author":"Q Zeng","year":"2023","unstructured":"Zeng Q, Lv Z, Li C, Shi Y, Lin Z, Liu C, Song G (2023) Fedprols: federated learning for iot perception data prediction. Appl Intell 53(3):3563\u20133575","journal-title":"Appl Intell"},{"key":"5426_CR16","first-page":"257","volume":"32","author":"C Chen","year":"2018","unstructured":"Chen C, Liu Z, Zhao P, Zhou J, Li X (2018) Privacy preserving point-of-interest recommendation using decentralized matrix factorization. Proceedings of the AAAI Conference on Artificial Intelligence 32:257\u2013264","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"5426_CR17","doi-asserted-by":"crossref","unstructured":"Long J, Chen T, Nguyen QVH, Xu G, Zheng K, Yin H (2023) Model-agnostic decentralized collaborative learning for on-device poi recommendation. In: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 423\u2013432","DOI":"10.1145\/3539618.3591733"},{"issue":"3","key":"5426_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3555374","volume":"41","author":"J Long","year":"2023","unstructured":"Long J, Chen T, Nguyen QVH, Yin H (2023) Decentralized collaborative learning framework for next poi recommendation. ACM Transactions on Information Systems 41(3):1\u201325","journal-title":"ACM Transactions on Information Systems"},{"key":"5426_CR19","doi-asserted-by":"crossref","unstructured":"Zhang Y, Liu B, Qian J (2023) Fedpjf: federated contrastive learning for privacy-preserving person-job fit. Applied Intelligence 1\u201312","DOI":"10.1007\/s10489-023-04775-2"},{"issue":"5","key":"5426_CR20","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1109\/MIS.2020.3014880","volume":"36","author":"D Chai","year":"2020","unstructured":"Chai D, Wang L, Chen K, Yang Q (2020) Secure federated matrix factorization. IEEE Intell Syst 36(5):11\u201320","journal-title":"IEEE Intell Syst"},{"key":"5426_CR21","doi-asserted-by":"crossref","unstructured":"Duriakova E, Tragos EZ, Smyth B, Hurley N, Pe\u00f1a FJ, Symeonidis P, Geraci J, Lawlor A (2019) Pdmfrec: a decentralised matrix factorisation with tunable user-centric privacy. In: Proceedings of the 13th ACM Conference on Recommender Systems, pp. 457\u2013461","DOI":"10.1145\/3298689.3347035"},{"key":"5426_CR22","doi-asserted-by":"crossref","unstructured":"Duriakova E, Hu\u00e1ng W, Tragos E, Lawlor A, Smyth B, Geraci J, Hurley N (2021) An algorithmic framework for decentralised matrix factorisation. In: Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2020, Ghent, Belgium, September 14\u201318, 2020, Proceedings, Part II, pp. 307\u2013323. Springer","DOI":"10.1007\/978-3-030-67661-2_19"},{"key":"5426_CR23","doi-asserted-by":"publisher","first-page":"449","DOI":"10.1016\/j.ins.2023.01.130","volume":"628","author":"L Wang","year":"2023","unstructured":"Wang L, Zhao X, Lu Z, Wang L, Zhang S (2023) Enhancing privacy preservation and trustworthiness for decentralized federated learning. Inf Sci 628:449\u2013468","journal-title":"Inf Sci"},{"issue":"21","key":"5426_CR24","doi-asserted-by":"publisher","first-page":"11118","DOI":"10.3390\/app122111118","volume":"12","author":"X Yang","year":"2022","unstructured":"Yang X, Luo Y, Fu S, Xu M, Chen Y (2022) Dpmf: Decentralized probabilistic matrix factorization for privacy-preserving recommendation. Appl Sci 12(21):11118","journal-title":"Appl Sci"},{"key":"5426_CR25","doi-asserted-by":"publisher","first-page":"688","DOI":"10.1016\/j.ins.2022.05.083","volume":"606","author":"Y Zhou","year":"2022","unstructured":"Zhou Y, Liu J, Wang JH, Wang J, Liu G, Wu D, Li C, Yu S (2022) Usst: A two-phase privacy-preserving framework for personalized recommendation with semi-distributed training. Inf Sci 606:688\u2013701","journal-title":"Inf Sci"},{"key":"5426_CR26","doi-asserted-by":"crossref","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, pp. 285\u2013295","DOI":"10.1145\/371920.372071"},{"key":"5426_CR27","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1609\/icwsm.v5i1.14109","volume":"5","author":"Z Cheng","year":"2011","unstructured":"Cheng Z, Caverlee J, Lee K, Sui D (2011) Exploring millions of footprints in location sharing services. Proceedings of the International AAAI Conference on Web and Social Media 5:81\u201388","journal-title":"Proceedings of the International AAAI Conference on Web and Social Media"},{"key":"5426_CR28","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1609\/aaai.v26i1.8100","volume":"26","author":"C Cheng","year":"2012","unstructured":"Cheng C, Yang H, King I, Lyu M (2012) Fused matrix factorization with geographical and social influence in location-based social networks. Proceedings of the AAAI Conference on Artificial Intelligence 26:17\u201323","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"5426_CR29","unstructured":"Rendle S, Freudenthaler C, Gantner Z, Schmidt-Thieme L (2012) Bpr: Bayesian personalized ranking from implicit feedback. arXiv:1205.2618"},{"key":"5426_CR30","doi-asserted-by":"crossref","unstructured":"Zhao T, McAuley J, King I (2014) Leveraging social connections to improve personalized ranking for collaborative filtering. In: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, pp. 261\u2013270","DOI":"10.1145\/2661829.2661998"},{"key":"5426_CR31","doi-asserted-by":"publisher","first-page":"1001","DOI":"10.1007\/s11280-018-0573-2","volume":"22","author":"S Hosseini","year":"2019","unstructured":"Hosseini S, Yin H, Zhou X, Sadiq S, Kangavari MR, Cheung NM (2019) Leveraging multi-aspect time-related influence in location recommendation. World Wide Web 22:1001\u20131028","journal-title":"World Wide Web"},{"issue":"21","key":"5426_CR32","doi-asserted-by":"publisher","first-page":"2673","DOI":"10.3390\/math9212673","volume":"9","author":"C Xu","year":"2021","unstructured":"Xu C, Liu D, Mei X (2021) Exploring an efficient poi recommendation model based on user characteristics and spatial-temporal factors. Mathematics 9(21):2673","journal-title":"Mathematics"},{"key":"5426_CR33","doi-asserted-by":"crossref","unstructured":"Lam SK, Frankowski D, Riedl J (2006) Do you trust your recommendations? an exploration of security and privacy issues in recommender systems. In: International Conference on Emerging Trends in Information and Communication Security, pp. 14\u201329. Springer","DOI":"10.1007\/11766155_2"},{"key":"5426_CR34","doi-asserted-by":"crossref","unstructured":"McSherry F, Mironov I (2009) Differentially private recommender systems: Building privacy into the netflix prize contenders. In: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 627\u2013636","DOI":"10.1145\/1557019.1557090"},{"key":"5426_CR35","doi-asserted-by":"crossref","unstructured":"Riboni D, Bettini C (2012) Private context-aware recommendation of points of interest: An initial investigation. In: 2012 IEEE International Conference on Pervasive Computing and Communications Workshops, pp. 584\u2013589. IEEE","DOI":"10.1109\/PerComW.2012.6197582"},{"key":"5426_CR36","doi-asserted-by":"publisher","first-page":"4224","DOI":"10.1609\/aaai.v35i5.16546","volume":"35","author":"F Liang","year":"2021","unstructured":"Liang F, Pan W, Ming Z (2021) Fedrec++: Lossless federated recommendation with explicit feedback. Proceedings of the AAAI Conference on Artificial Intelligence 35:4224\u20134231","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"5426_CR37","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. arXiv:1901.09888"},{"key":"5426_CR38","doi-asserted-by":"crossref","unstructured":"Li D, Chen C, Lv Q, Shang L, Zhao Y, Lu T, Gu N (2016) An algorithm for efficient privacy-preserving item-based collaborative filtering. Futur Gener Comput Syst 55:311\u2013320","DOI":"10.1016\/j.future.2014.11.003"},{"issue":"5","key":"5426_CR39","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3394138","volume":"11","author":"C Chen","year":"2020","unstructured":"Chen C, Zhou J, Wu B, Fang W, Wang L, Qi Y, Zheng X (2020) Practical privacy preserving poi recommendation. ACM Transactions on Intelligent Systems and Technology (TIST) 11(5):1\u201320","journal-title":"ACM Transactions on Intelligent Systems and Technology (TIST)"},{"key":"5426_CR40","doi-asserted-by":"publisher","first-page":"767","DOI":"10.1016\/j.ins.2022.12.024","volume":"623","author":"V Perifanis","year":"2023","unstructured":"Perifanis V, Drosatos G, Stamatelatos G, Efraimidis PS (2023) Fedpoirec: Privacy-preserving federated poi recommendation with social influence. Inf Sci 623:767\u2013790","journal-title":"Inf Sci"},{"key":"5426_CR41","unstructured":"Ying S (2020) Shared mf: A privacy-preserving recommendation system. arXiv:2008.07759"},{"key":"5426_CR42","unstructured":"Mnih A, Salakhutdinov R (2007) Probabilistic matrix factorization. In advances in neural information processing systems. Advances in Neural Information Processing Systems"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-024-05426-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-024-05426-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-024-05426-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,16]],"date-time":"2024-11-16T12:00:19Z","timestamp":1731758419000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-024-05426-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4]]},"references-count":42,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2024,4]]}},"alternative-id":["5426"],"URL":"https:\/\/doi.org\/10.1007\/s10489-024-05426-w","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,4]]},"assertion":[{"value":"27 March 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 April 2024","order":2,"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 that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"competing interest"}},{"value":"We confirm that all data used in this study were obtained in accordance with ethical principles and informed consent procedures. All data used in this manuscript was obtained with the informed consent of participants.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical and informed consent for data used"}}]}}