{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T17:32:09Z","timestamp":1786123929734,"version":"3.56.0"},"reference-count":55,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","license":[{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,10,1]],"date-time":"2023-10-01T00:00:00Z","timestamp":1696118400000},"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":["62206002"],"award-info":[{"award-number":["62206002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003995","name":"Anhui Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["2208085QF195"],"award-info":[{"award-number":["2208085QF195"]}],"id":[{"id":"10.13039\/501100003995","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003995","name":"Anhui Provincial Natural Science Foundation","doi-asserted-by":"publisher","award":["2208085QF199"],"award-info":[{"award-number":["2208085QF199"]}],"id":[{"id":"10.13039\/501100003995","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000923","name":"Australia Research Council (ARC) Linkage Projects","doi-asserted-by":"publisher","award":["LP210100129"],"award-info":[{"award-number":["LP210100129"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Comput. Soc. Syst."],"published-print":{"date-parts":[[2023,10]]},"DOI":"10.1109\/tcss.2023.3268683","type":"journal-article","created":{"date-parts":[[2023,5,16]],"date-time":"2023-05-16T19:48:10Z","timestamp":1684266490000},"page":"2660-2671","source":"Crossref","is-referenced-by-count":26,"title":["Adversarial Heterogeneous Graph Neural Network for Robust Recommendation"],"prefix":"10.1109","volume":"10","author":[{"given":"Lei","family":"Sang","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Anhui University, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9581-8849","authenticated-orcid":false,"given":"Min","family":"Xu","sequence":"additional","affiliation":[{"name":"Faculty of Engineering and Information Technology, University of Technology Sydney, Sydney, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9488-2208","authenticated-orcid":false,"given":"Shengsheng","family":"Qian","sequence":"additional","affiliation":[{"name":"Institute of Automation, Chinese Academy of Sciences, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2396-1704","authenticated-orcid":false,"given":"Xindong","family":"Wu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Knowledge Engineering with Big Data (the Ministry of Education of China), Hefei University of Technology, Hefei, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3351034"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219890"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2833443"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.aiopen.2022.03.002"},{"key":"ref53","article-title":"Batch virtual adversarial training for graph convolutional networks","author":"deng","year":"2019","journal-title":"arXiv 1902 09192"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.03.053"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2022.3181065"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00016"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482291"},{"key":"ref54","first-page":"1","article-title":"Latent adversarial training of graph convolution networks","volume":"2","author":"jin","year":"2019","journal-title":"Proc ICML Workshop Learn Reasoning Graph-Structured Represent"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113992"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-16-6166-2"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.12.067"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330961"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2022.3151822"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1145\/3488560.3501396"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v28i1.8917"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/2806416.2806528"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939673"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186175"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1401944"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/2647868.2654920"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE51399.2021.00208"},{"key":"ref43","first-page":"452","article-title":"BPR: Bayesian personalized ranking from implicit feedback","author":"rendle","year":"2009","journal-title":"Proc 25th Conf Uncertainty Artif Intell (AUAI)"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2022.3214308"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401063"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2020.3007330"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.10.110"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TGCN.2022.3165262"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2022.3176403"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i01.5360"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2020.3023155"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3209981"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2020.3004059"},{"key":"ref34","article-title":"Graph attention networks","author":"veli?kovi?","year":"2017","journal-title":"arXiv 1710 10903"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531763"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2858821"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3331184.3331267"},{"key":"ref30","article-title":"Adversarial attacks and defenses on graphs: A review, a tool and empirical studies","author":"jin","year":"2020","journal-title":"arXiv 2003 00653"},{"key":"ref33","first-page":"1024","article-title":"Inductive representation learning on large graphs","author":"hamilton","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-16142-2_1"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3123266.3123433"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3145690"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2893638"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2020.3042628"},{"key":"ref24","article-title":"Graph adversarial training: Dynamically regularizing based on graph structure","author":"feng","year":"2019","journal-title":"arXiv 1902 08226"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2021.3064213"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401165"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3274694.3274706"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3447556.3447566"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TCSS.2020.3013878"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/872"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-018-9655-x"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/1097047.1097061"},{"key":"ref29","first-page":"1","article-title":"Explaining and harnessing adversarial examples","author":"goodfellow","year":"2015","journal-title":"Proc Int Conf Learn Represent"}],"container-title":["IEEE Transactions on Computational Social Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6570650\/10268617\/10124876.pdf?arnumber=10124876","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T18:21:57Z","timestamp":1698085317000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10124876\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10]]},"references-count":55,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/tcss.2023.3268683","relation":{},"ISSN":["2329-924X","2373-7476"],"issn-type":[{"value":"2329-924X","type":"electronic"},{"value":"2373-7476","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,10]]}}}