{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T14:30:28Z","timestamp":1773930628704,"version":"3.50.1"},"reference-count":56,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"8","license":[{"start":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T00:00:00Z","timestamp":1659312000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T00:00:00Z","timestamp":1659312000000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T00:00:00Z","timestamp":1659312000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T00:00:00Z","timestamp":1659312000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072077"],"award-info":[{"award-number":["62072077"]}],"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":["61602097"],"award-info":[{"award-number":["61602097"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","award":["CNS 1646107"],"award-info":[{"award-number":["CNS 1646107"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Cybern."],"published-print":{"date-parts":[[2022,8]]},"DOI":"10.1109\/tcyb.2021.3049533","type":"journal-article","created":{"date-parts":[[2021,2,3]],"date-time":"2021-02-03T06:10:50Z","timestamp":1612332650000},"page":"8128-8141","source":"Crossref","is-referenced-by-count":11,"title":["MetaMove: On Improving Human Mobility Classification and Prediction via Metalearning"],"prefix":"10.1109","volume":"52","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8038-8150","authenticated-orcid":false,"given":"Fan","family":"Zhou","sequence":"first","affiliation":[{"name":"School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China"}]},{"given":"Xin","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8163-3146","authenticated-orcid":false,"given":"Tings","family":"Zhong","sequence":"additional","affiliation":[{"name":"School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8839-6278","authenticated-orcid":false,"given":"Goce","family":"Trajcevski","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Iowa State University, Ames, IA, USA"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2866809"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3161602"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/SURV.2013.042313.00197"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2018.1700569"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.2019.2931723"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2017.2748987"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2019.05.004"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2972062"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186058"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313610"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2018.2861897"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/s11280-020-00824-9"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2020.102912"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2019.2945999"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623638"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313609"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref18","article-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling","author":"Chung","year":"2014"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/446"},{"key":"ref20","article-title":"Optimization as a model for few-shot learning","volume-title":"Proc. ICLR","author":"Sachin"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4615-5529-2_8"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1126\/science.aab3050"},{"key":"ref23","first-page":"4077","article-title":"Prototypical networks for few-shot learning","volume-title":"Proc. NIPS","author":"Snell"},{"key":"ref24","first-page":"1842","article-title":"Meta-learning with memory-augmented neural networks","volume-title":"Proc. ICML","author":"Santoro"},{"key":"ref25","article-title":"Few-shot learning with graph neural networks","volume-title":"Proc. ICLR","author":"Satorras"},{"key":"ref26","first-page":"1126","article-title":"Model-agnostic meta-learning for fast adaptation of deep networks","volume-title":"Proc. ICML","author":"Chelsea"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/234"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N18-1202"},{"key":"ref29","volume-title":"Reptile: A scalable metalearning algorithm","author":"Nichol","year":"2018"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098094"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/2661829.2661983"},{"key":"ref32","article-title":"Meta-learning for semi-supervised few-shot classification","volume-title":"Proc. ICLR","author":"Ren"},{"key":"ref33","volume-title":"Semi-supervised few-shot learning with local and global consistency","author":"Ayyad","year":"2019"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v30i1.9971"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10500"},{"key":"ref36","first-page":"512","article-title":"Boosting algorithms as gradient descent","volume-title":"Proc. NIPS","author":"Mason"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/2484028.2484030"},{"key":"ref39","first-page":"2069","article-title":"Personalized ranking metric embedding for next new POI recommendation","volume-title":"Proc. IJCAI","author":"Feng"},{"key":"ref40","volume-title":"Efficient estimation of word representations in vector space","author":"Mikolov","year":"2013"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1024691352"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.3009280"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.2974494"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3005325"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2020.03.010"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/3293318"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2019.2930744"},{"key":"ref48","first-page":"3630","article-title":"Matching networks for one shot learning","volume-title":"Proc. NIPS","author":"Vinyals"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00131"},{"key":"ref50","article-title":"Meta-learning with differentiable closed-form solvers","volume-title":"ICLR","author":"Bertinetto"},{"key":"ref51","first-page":"2554","article-title":"Meta networks","volume-title":"Proc. ICML","author":"Munkhdalai"},{"key":"ref52","article-title":"Meta-learning with latent embedding optimization","volume-title":"Proc. ICLR","author":"Rusu"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313577"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2018.2820174"},{"key":"ref55","first-page":"6904","article-title":"A meta-learning perspective on cold-start recommendations for items","volume-title":"Proc. NIPS","author":"Vartak"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.5555\/3045390.3045502"}],"container-title":["IEEE Transactions on Cybernetics"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielam\/6221036\/9833007\/9345475-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6221036\/9833007\/09345475.pdf?arnumber=9345475","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,9]],"date-time":"2024-01-09T22:42:36Z","timestamp":1704840156000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9345475\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8]]},"references-count":56,"journal-issue":{"issue":"8"},"URL":"https:\/\/doi.org\/10.1109\/tcyb.2021.3049533","relation":{},"ISSN":["2168-2267","2168-2275"],"issn-type":[{"value":"2168-2267","type":"print"},{"value":"2168-2275","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,8]]}}}