{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T16:29:42Z","timestamp":1775579382737,"version":"3.50.1"},"reference-count":52,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,7,1]],"date-time":"2023-07-01T00:00:00Z","timestamp":1688169600000},"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":["71971002"],"award-info":[{"award-number":["71971002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2019A1515011792"],"award-info":[{"award-number":["2019A1515011792"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003995","name":"Natural Science Foundation of Anhui Province","doi-asserted-by":"publisher","award":["1908085QF283"],"award-info":[{"award-number":["1908085QF283"]}],"id":[{"id":"10.13039\/501100003995","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Netw. Sci. Eng."],"published-print":{"date-parts":[[2023,7,1]]},"DOI":"10.1109\/tnse.2023.3243058","type":"journal-article","created":{"date-parts":[[2023,2,7]],"date-time":"2023-02-07T18:58:16Z","timestamp":1675796296000},"page":"2098-2108","source":"Crossref","is-referenced-by-count":22,"title":["RAHG: A Role-Aware Hypergraph Neural Network for Node Classification in Graphs"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4952-0969","authenticated-orcid":false,"given":"Kunhao","family":"Li","sequence":"first","affiliation":[{"name":"School of Internet, Anhui University, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0389-9061","authenticated-orcid":false,"given":"Zhenhua","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Internet, Anhui University, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6607-7025","authenticated-orcid":false,"given":"Zhaohong","family":"Jia","sequence":"additional","affiliation":[{"name":"School of Internet, Anhui University, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref13","article-title":"Variational graph auto-encoders","author":"kipf","year":"2016"},{"key":"ref12","first-page":"1025","article-title":"Inductive representation learning on large graphs","volume":"30","author":"hamilton","year":"2017","journal-title":"Proc Int Conf Adv Neural Inf Process Syst"},{"key":"ref15","first-page":"1263","article-title":"Neural message passing for quantum chemistry","author":"gilmer","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref14","article-title":"How powerful are graph neural networks?","author":"xu","year":"2019","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref52","article-title":"Fast graph representation learning with PyTorch Geometric","author":"fey","year":"0","journal-title":"Proc Int Conf Learn Representations Workshop Representation Learn Graphs Manifolds"},{"key":"ref11","article-title":"Graph attention networks","author":"veli?kovi?","year":"2018","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref10","article-title":"Semi-supervised classification with graph convolutional networks","author":"kipf","year":"2017","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/2339530.2339723"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9164"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220025"},{"key":"ref18","first-page":"1","article-title":"role2vec: Role-based network embeddings","author":"ahmed","year":"0","journal-title":"Proc 8th Int Workshop Deep Learn Graphs Methods Appl"},{"key":"ref51","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"maaten","year":"2008","journal-title":"J Mach Learn Res"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1038\/nbt1206-1565"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bti1007"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/s00607-018-0659-9"},{"key":"ref48","first-page":"271","article-title":"Event classification and relationship labeling in affiliation networks","author":"zhao","year":"0","journal-title":"Proc Workshop Stat Netw Anal 23rd Int Conf Mach Learn"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v29i1.9277"},{"key":"ref42","article-title":"Hyper-SAGNN: A self-attention based graph neural network for hypergraphs","author":"zhang","year":"2020","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107637"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3531868"},{"key":"ref43","article-title":"You are allset: A multiset function framework for hypergraph neural networks","author":"chien","year":"2022","journal-title":"Proc Int Conf Learn Representations"},{"key":"ref49","article-title":"Revisiting semi-supervised learning with graph embeddings","author":"yang","year":"2016"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.aiopen.2021.01.001"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-77766-9"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.2981333"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE48307.2020.00149"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICWS53863.2021.00026"},{"key":"ref6","article-title":"Meta-learning GNN initializations for low-resource molecular property prediction","author":"nguyen","year":"2020","journal-title":"Proc 4th Lifelong Mach Learn Workshop ICML"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3094295"},{"key":"ref40","first-page":"1511","article-title":"HyperGCN: A new method for training graph convolutional networks on hypergraphs","volume":"32","author":"yadati","year":"0","journal-title":"Proc Int Conf Adv Neural Inf Process Syst"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939753"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/2736277.2741093"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2022.07.035"},{"key":"ref36","first-page":"28877","article-title":"Do transformers really perform badly for graph representation?","volume":"34","author":"ying","year":"2021","journal-title":"Proc Int Conf Adv Neural Inf Process Syst"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623732"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1017\/ATSIP.2020.13"},{"key":"ref33","article-title":"Efficient estimation of word representations in vector space","author":"mikolov","year":"2013"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939754"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106227"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.106746"},{"key":"ref39","first-page":"1601","article-title":"Learning with hypergraphs: Clustering, classification, and embedding","author":"zhou","year":"0","journal-title":"Proc Int Conf Adv Neural Inf Process Syst"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098061"},{"key":"ref24","first-page":"3469","article-title":"Structure-aware transformer for graph representation learning","author":"chen","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref23","article-title":"Hyperbolic graph neural networks: A review of methods and applications","author":"yang","year":"2022"},{"key":"ref26","first-page":"7134","article-title":"Position-aware graph neural networks","author":"you","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i12.17283"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33013558"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401063"},{"key":"ref21","first-page":"3844","article-title":"Convolutional neural networks on graphs with fast localized spectral filtering","volume":"29","author":"defferrard","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00543"},{"key":"ref27","first-page":"13 242","article-title":"Finding global homophily in graph neural networks when meeting heterophily","author":"li","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref29","article-title":"Graph wavelet neural network","author":"xu","year":"2019","journal-title":"Proc Int Conf Learn Representations"}],"container-title":["IEEE Transactions on Network Science and Engineering"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6488902\/10159461\/10039676.pdf?arnumber=10039676","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,15]],"date-time":"2024-01-15T21:29:08Z","timestamp":1705354148000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10039676\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,1]]},"references-count":52,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/tnse.2023.3243058","relation":{},"ISSN":["2327-4697","2334-329X"],"issn-type":[{"value":"2327-4697","type":"electronic"},{"value":"2334-329X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7,1]]}}}