{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T05:15:44Z","timestamp":1781759744974,"version":"3.54.5"},"reference-count":54,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T00:00:00Z","timestamp":1654041600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T00:00:00Z","timestamp":1654041600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,6,1]],"date-time":"2022-06-01T00:00:00Z","timestamp":1654041600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2020AAA0103800"],"award-info":[{"award-number":["2020AAA0103800"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61976198"],"award-info":[{"award-number":["61976198"]}],"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":["62022077"],"award-info":[{"award-number":["62022077"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["WK2150110017"],"award-info":[{"award-number":["WK2150110017"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2022,6]]},"DOI":"10.1109\/tnnls.2021.3136171","type":"journal-article","created":{"date-parts":[[2022,1,4]],"date-time":"2022-01-04T20:28:39Z","timestamp":1641328119000},"page":"2416-2428","source":"Crossref","is-referenced-by-count":112,"title":["Graph Convolutional Adversarial Networks for Spatiotemporal Anomaly Detection"],"prefix":"10.1109","volume":"33","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1723-6450","authenticated-orcid":false,"given":"Leyan","family":"Deng","sequence":"first","affiliation":[{"name":"School of Data Science, University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3507-9607","authenticated-orcid":false,"given":"Defu","family":"Lian","sequence":"additional","affiliation":[{"name":"School of Data Science, University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1661-0420","authenticated-orcid":false,"given":"Zhenya","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4835-4102","authenticated-orcid":false,"given":"Enhong","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Data Science, University of Science and Technology of China, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/2629592"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2020.2991008"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3191786"},{"key":"ref4","first-page":"2500","article-title":"A collaborative filtering approach to citywide human mobility completion from sparse call records","volume-title":"Proc. IJCAI","author":"Fan"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/PerCom.2013.6526736"},{"key":"ref6","volume-title":"Melbourne 2030: A Planning Update Melbourne@ 5 Million","year":"2008"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.3390\/s16060868"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2011.65"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/2597181"},{"key":"ref10","article-title":"Open government data: Towards empirical analysis of open government data initiatives","author":"Ubaldi","year":"2013"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1038\/nature06958"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/506"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/2700478"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/UIC-ATC-ScalCom-CBDCom-IoP.2015.43"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/BigData.2017.8258039"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/2346496.2346521"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/1871437.1871716"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2009.230"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3007540.3007545"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2014.2305334"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/2346496.2346518"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206641"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-25856-5_18"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/iThings\/CPSCom.2011.25"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/2494091.2497352"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.trb.2016.06.011"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/2632048.2636073"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/s10618-018-0560-3"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/THMS.2016.2596103"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2915231"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/SAHCN.2019.8824981"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/837"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.3156\/jsoft.29.5_177_2"},{"key":"ref34","article-title":"Deep learning for anomaly detection: A review","volume-title":"arXiv:2007.02500","author":"Pang","year":"2020"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-59050-9_12"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-20893-6_39"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-30490-4_56"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2018.8462388"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2017.8296547"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/2820783.2820813"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2235192"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-04167-0_33"},{"key":"ref43","article-title":"Spatio-temporal graph convolutional networks: A deep learning framework for traffic forecasting","volume-title":"arXiv:1709.04875","author":"Yu","year":"2017"},{"key":"ref44","article-title":"Empirical evaluation of gated recurrent neural networks on sequence modeling","volume-title":"arXiv:1412.3555","author":"Chung","year":"2014"},{"key":"ref45","article-title":"Diffusion convolutional recurrent neural network: Data-driven traffic forecasting","volume-title":"arXiv:1707.01926","author":"Li","year":"2017"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/2525314.2525343"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.17"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.2307\/1270566"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1145\/342009.335388"},{"issue":"1","key":"ref50","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.2307\/1912017"},{"key":"ref52","doi-asserted-by":"crossref","DOI":"10.2307\/j.ctv14jx6sm","volume-title":"Time Series Analysis","author":"Hamilton","year":"2020"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301922"},{"key":"ref54","article-title":"Adam: A method for stochastic optimization","volume-title":"arXiv:1412.6980","author":"Kingma","year":"2014"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/9786556\/09669110.pdf?arnumber=9669110","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,13]],"date-time":"2024-01-13T21:46:38Z","timestamp":1705182398000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9669110\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6]]},"references-count":54,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2021.3136171","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,6]]}}}