{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T15:54:33Z","timestamp":1774022073464,"version":"3.50.1"},"reference-count":49,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Netw. Sci. Eng."],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/tnse.2023.3266752","type":"journal-article","created":{"date-parts":[[2023,4,13]],"date-time":"2023-04-13T17:50:16Z","timestamp":1681408216000},"page":"1-18","source":"Crossref","is-referenced-by-count":18,"title":["GNN-Geo: A Graph Neural Network-based Fine-grained IP geolocation Framework"],"prefix":"10.1109","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7565-1778","authenticated-orcid":false,"given":"Shichang","family":"Ding","sequence":"first","affiliation":[{"name":"State Key Laboratory of Mathematical Engineering and Advanced Computing, Zhengzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3225-4649","authenticated-orcid":false,"given":"xiangyang","family":"Luo","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Mathematical Engineering and Advanced Computing, Zhengzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4971-3365","authenticated-orcid":false,"given":"Jinwei","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer and Software, Nanjing University of Information Science & Technology, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8012-4753","authenticated-orcid":false,"given":"Xiaoming","family":"Fu","sequence":"additional","affiliation":[{"name":"Institute of Computer Science, University of Göttingen, Göttingen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/541"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462862"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3442442.3451888"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482424"},{"key":"ref11","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2016"},{"key":"ref10","article-title":"Benchmarking graph neural networks","author":"dwivedi","year":"2020"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2021.3057881"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2021.3089435"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2020.3038218"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2020.3041529"},{"key":"ref46","article-title":"IPvSeeYou: Exploiting leaked identifiers in IPv6 for street-level geolocation","author":"rye","year":"2022"},{"key":"ref45","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref48","article-title":"Grid search, random search, genetic algorithm: A big comparison for NAS","author":"liashchynskyi","year":"2019"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2018.02.006"},{"key":"ref42","article-title":"Deep learning using rectified linear units (ReLU)","author":"agarap","year":"2018"},{"key":"ref41","article-title":"Automating botnet detection with graph neural networks","author":"zhou","year":"2020"},{"key":"ref44","article-title":"How powerful are graph neural networks","author":"xu","year":"2018"},{"key":"ref43","first-page":"1025","article-title":"Inductive representation learning on large graphs","author":"hamilton","year":"0","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref49","first-page":"2488","article-title":"How does batch normalization help optimization?","author":"santurkar","year":"0","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/INFCOMW.2016.7562066"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1186\/s13640-020-00504-8"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3457611"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3366423.3380216"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2014.6847987"},{"key":"ref5","first-page":"365","article-title":"Towards street-level client-independent IP geolocation","author":"wang","year":"0","journal-title":"Proc 8th USENIX Symp Netw Syst Des Implementation"},{"key":"ref40","article-title":"Spatiotemporal graph convolutional recurrent networks for traffic matrix prediction","volume":"31","author":"jianlong","year":"0","journal-title":"Trans Emerg Telecommun Technol"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM.2019.8737496"},{"key":"ref34","article-title":"Applying graph-based deep learning to realistic network scenarios","author":"galmes","year":"0"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/LCOMM.2018.2886259"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2020.3025806"},{"key":"ref31","article-title":"Designing weighted and multiplex networks for deep learning user geolocation in twitter","author":"funes","year":"2021"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-89363-7_33"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/3360468.3366773"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/3434239"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/6658642"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2021.3073926"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ICC40277.2020.9149277"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/BigData50022.2020.9512748"},{"key":"ref24","first-page":"1263","article-title":"Neural message passing for quantum chemistry","author":"gilmer","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref23","article-title":"Graph attention networks","author":"veli?kovi?","year":"2017"},{"key":"ref26","article-title":"Utilizing edge features in graph neural networks via variational information maximization","author":"chen","year":"2019"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2020.3044299"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1016\/j.comcom.2021.12.015"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-022-12306-3"},{"key":"ref28","article-title":"Adaptive visibility graph neural network and its application in modulation classification","author":"xuan","year":"2021"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2021.11.004"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.116240"}],"container-title":["IEEE Transactions on Network Science and Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6488902\/6930788\/10102310.pdf?arnumber=10102310","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,24]],"date-time":"2023-10-24T22:37:55Z","timestamp":1698187075000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10102310\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":49,"URL":"https:\/\/doi.org\/10.1109\/tnse.2023.3266752","relation":{},"ISSN":["2327-4697","2334-329X"],"issn-type":[{"value":"2327-4697","type":"electronic"},{"value":"2334-329X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}