{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T08:12:06Z","timestamp":1782979926311,"version":"3.54.5"},"reference-count":43,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Knowl. Data Eng."],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/tkde.2021.3089763","type":"journal-article","created":{"date-parts":[[2021,6,16]],"date-time":"2021-06-16T19:56:46Z","timestamp":1623873406000},"page":"1-1","source":"Crossref","is-referenced-by-count":8,"title":["Finding Critical Users in Social Communities via Graph Convolutions"],"prefix":"10.1109","author":[{"given":"Kangfei","family":"Zhao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiwei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Rong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeffrey Xu","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junzhou","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2849727"},{"key":"ref38","first-page":"52","article-title":"Representation learning on graphs: Methods and applications","volume":"40","author":"hamilton","year":"2017","journal-title":"IEEE Data Eng Bull"},{"key":"ref33","first-page":"2692","article-title":"Pointer networks","author":"vinyals","year":"2015","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref32","article-title":"Neural combinatorial optimization with reinforcement learning","author":"bello","year":"2016","journal-title":"CoRR"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-31585-5_40"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D16-1191"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33012314"},{"key":"ref36","first-page":"537","article-title":"Combinatorial optimization with graph convolutional networks and guided tree search","author":"li","year":"2018","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/BF00992696"},{"key":"ref34","first-page":"6348","article-title":"Learning combinatorial optimization algorithms over graphs","author":"khalil","year":"2017","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref10","article-title":"Spectral networks and locally connected networks on graphs","author":"bruna","year":"2014","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2014.119"},{"key":"ref11","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2017","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3308558.3313461"},{"key":"ref13","first-page":"5998","article-title":"Attention is all you need","author":"vaswani","year":"2017","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11604"},{"key":"ref15","article-title":"SNAP Datasets: Stanford large network dataset collection","author":"leskovec","year":"2014"},{"key":"ref16","article-title":"KONECT (the koblenz network collection)","year":"0"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9277"},{"key":"ref18","article-title":"Pytorch","year":"0"},{"key":"ref19","article-title":"Pybind11-Seamless operability between C++11 and Python","year":"0"},{"key":"ref28","first-page":"541","article-title":"How robust is the core of a network?","author":"adiga","year":"2013","journal-title":"Machine Learning and Knowledge Discovery in Databases"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3269206.3269254"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/0378-8733(83)90028-X"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-91452-7_28"},{"key":"ref6","first-page":"3391","article-title":"Deep sets","author":"zaheer","year":"2017","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref29","first-page":"248","article-title":"Degeneracy-based real-time sub-event detection in twitter stream","author":"meladianos","year":"2015","journal-title":"Proc AAAI Press"},{"key":"ref5","article-title":"Approximation with artificial neural networks","volume":"24","author":"cs\u00e1ji","year":"2001","journal-title":"J Fac Sci"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623732"},{"key":"ref7","first-page":"1201","article-title":"Graph kernels","volume":"11","author":"vishwanathan","year":"2010","journal-title":"J Mach Learn Res"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3186127"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939754"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10482"},{"key":"ref20","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2015","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1086\/228631"},{"key":"ref21","article-title":"The pagerank citation ranking: Bringing order to the web","author":"page","year":"1999","journal-title":"Tech Rep"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10488"},{"key":"ref24","article-title":"Exploring network structure, dynamics, and function using networkx","author":"hagberg","year":"2008","journal-title":"Tech Rep LA-UR-08&#x2013;05495"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/2736277.2741093"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1038\/30918"},{"key":"ref26","first-page":"79","article-title":"A parameterized complexity view on collapsing k-cores","author":"luo","year":"2018","journal-title":"Proc IPEC"},{"key":"ref43","article-title":"A comprehensive survey on graph neural networks","author":"wu","year":"2019"},{"key":"ref25","article-title":"K-core minimization: A game theoretic approach","author":"medya","year":"2019"}],"container-title":["IEEE Transactions on Knowledge and Data Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/69\/4358933\/09457127.pdf?arnumber=9457127","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,8]],"date-time":"2022-12-08T15:27:45Z","timestamp":1670513265000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9457127\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":43,"URL":"https:\/\/doi.org\/10.1109\/tkde.2021.3089763","relation":{},"ISSN":["1041-4347","1558-2191","2326-3865"],"issn-type":[{"value":"1041-4347","type":"print"},{"value":"1558-2191","type":"electronic"},{"value":"2326-3865","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]}}}