{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:25:26Z","timestamp":1760059526306,"version":"build-2065373602"},"reference-count":42,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"20","license":[{"start":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T00:00:00Z","timestamp":1760486400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T00:00:00Z","timestamp":1760486400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T00:00:00Z","timestamp":1760486400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["ZYGX2019Z014"],"award-info":[{"award-number":["ZYGX2019Z014"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61976044","52079026"],"award-info":[{"award-number":["61976044","52079026"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Internet Things J."],"published-print":{"date-parts":[[2025,10,15]]},"DOI":"10.1109\/jiot.2025.3592954","type":"journal-article","created":{"date-parts":[[2025,7,28]],"date-time":"2025-07-28T19:51:00Z","timestamp":1753732260000},"page":"42103-42115","source":"Crossref","is-referenced-by-count":0,"title":["Federated Learning on Multilabel Evolving Data Streams"],"prefix":"10.1109","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7593-4594","authenticated-orcid":false,"given":"Khalid Odartey","family":"Lamptey","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Donghua University, Shanghai, China"}]},{"given":"Browne Judith","family":"Ayekai","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4145-7176","authenticated-orcid":false,"given":"Salah","family":"Ud Din","sequence":"additional","affiliation":[{"name":"EIT Data Science and Communication College, Zhejiang Yuexiu University, Shaoxing, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3051276"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.3233\/JIFS-211100"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2020.2975749"},{"key":"ref4","article-title":"FLAG: Fast label-adaptive aggregation for multi-label classification in federated learning","author":"Chang","year":"2023","journal-title":"arXiv:2302.13571"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.3390\/app13042713"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.106775"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2013.39"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.06.001"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2022.01.075"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2810872"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3363573"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.107965"},{"key":"ref13","first-page":"23","article-title":"Multi-label knn classifier with self adjusting memory for drifting data streams","volume-title":"Proc. 2nd Int. Workshop Learn. Imbalanced Domains, Theory Appl.","author":"Roseberry"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3271774"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-022-03414-6"},{"article-title":"Goowe-ML: A novel online stacked ensemble for multi-label classification in data streams","year":"2019","author":"B\u00fcy\u00fck\u00e7ak\u00edr","key":"ref16"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3329061"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI48211.2021.9433876"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/BigDataSecurityHPSCIDS54978.2022.00049"},{"key":"ref20","article-title":"Federated learning for data streams","author":"Marfoq","year":"2023","journal-title":"arXiv:2301.01542"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/BigData50022.2020.9378161"},{"key":"ref22","first-page":"12073","article-title":"Federated continual learning with weighted inter-client transfer","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Yoon"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2024.3522812"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2020.2989213"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/MCI.2015.2471196"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.01.078"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3200068"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2018.2869476"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108216"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2022.02.024"},{"key":"ref31","article-title":"Transductive multi-label zero-shot learning","author":"Fu","year":"2015","journal-title":"arXiv:1503.07790"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2016.2522412"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2020.3027509"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2006.12.019"},{"key":"ref35","article-title":"Federated optimization in heterogeneous networks","author":"Li","year":"2018","journal-title":"arXiv:1812.06127"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-011-5256-5"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2013.10.006"},{"key":"ref38","first-page":"7252","article-title":"Bayesian nonparametric federated learning of neural networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Yurochkin"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2015.14"},{"key":"ref40","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. Artif. Intell. Stat.","author":"McMahan"},{"key":"ref41","article-title":"Fedbn: Federated learning on non-IID features via local batch normalization","author":"Li","year":"2021","journal-title":"arXiv:2102.07623"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-022-10232-2"}],"container-title":["IEEE Internet of Things Journal"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6488907\/11197149\/11098479.pdf?arnumber=11098479","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T17:55:05Z","timestamp":1760032505000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11098479\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,15]]},"references-count":42,"journal-issue":{"issue":"20"},"URL":"https:\/\/doi.org\/10.1109\/jiot.2025.3592954","relation":{},"ISSN":["2327-4662","2372-2541"],"issn-type":[{"type":"electronic","value":"2327-4662"},{"type":"electronic","value":"2372-2541"}],"subject":[],"published":{"date-parts":[[2025,10,15]]}}}