{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T20:09:24Z","timestamp":1784059764464,"version":"3.55.0"},"reference-count":49,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62306224"],"award-info":[{"award-number":["62306224"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neurocomputing"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.neucom.2026.134432","type":"journal-article","created":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T06:44:40Z","timestamp":1783147480000},"page":"134432","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["MASCN: Multi-view attribute-structure consistency network for contrastive deep graph clustering"],"prefix":"10.1016","volume":"700","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5964-0123","authenticated-orcid":false,"given":"Xiangyi","family":"Teng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-1333-2346","authenticated-orcid":false,"given":"Hongbin","family":"Cao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nina","family":"Shu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"1","key":"10.1016\/j.neucom.2026.134432_bib0005","article-title":"From social networks to knowledge graphs: a plea for interdisciplinary approaches","volume":"6","author":"D\u00f6rpinghaus","year":"2022","journal-title":"Soc. Sci. Humanit. Open"},{"key":"10.1016\/j.neucom.2026.134432_bib0010","series-title":"Proceedings of the ACM Web Conference 2022","first-page":"1475","article-title":"Generating simple directed social network graphs for information spreading","author":"Schweimer","year":"2022"},{"issue":"118024","key":"10.1016\/j.neucom.2026.134432_bib0015","article-title":"FUNC: finding critical nodes in uncertain networks through deep reinforcement learning","volume":"207","author":"Ma","year":"2026","journal-title":"Chaos Solitons Fractals"},{"issue":"1","key":"10.1016\/j.neucom.2026.134432_bib0020","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1109\/TCYB.2019.2931983","article-title":"Overlapping community detection in directed and undirected attributed networks using a multiobjective evolutionary algorithm","volume":"51","author":"Teng","year":"2019","journal-title":"IEEE Trans. Cybern."},{"key":"10.1016\/j.neucom.2026.134432_bib0025","series-title":"Proceedings of the ACM Web Conference 2022","first-page":"1944","article-title":"Fast variational autoencoder with inverted multi-index for collaborative filtering","author":"Chen","year":"2022"},{"key":"10.1016\/j.neucom.2026.134432_bib0030","series-title":"Proceedings of the ACM Web Conference 2022","first-page":"1997","article-title":"Learning recommenders for implicit feedback with importance resampling","author":"Chen","year":"2022"},{"key":"10.1016\/j.neucom.2026.134432_bib0035","doi-asserted-by":"crossref","first-page":"34817","DOI":"10.52202\/068431-2523","article-title":"Cache-augmented inbatch importance resampling for training recommender retriever","volume":"35","author":"Chen","year":"2022","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"9","key":"10.1016\/j.neucom.2026.134432_bib0040","doi-asserted-by":"crossref","first-page":"4935","DOI":"10.1109\/TKDE.2025.3581963","article-title":"A universal subhypergraph-assisted embedding framework for both homogeneous and heterogeneous networks","volume":"37","author":"Mo","year":"2025","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"1","key":"10.1016\/j.neucom.2026.134432_bib0045","doi-asserted-by":"crossref","first-page":"4256","DOI":"10.1038\/s41467-020-18112-5","article-title":"Reconciling qualitative, abstract, and scalable modeling of biological networks","volume":"11","author":"Paulev\u00e9","year":"2020","journal-title":"Nat. Commun."},{"issue":"1","key":"10.1016\/j.neucom.2026.134432_bib0050","doi-asserted-by":"crossref","first-page":"964","DOI":"10.1038\/s41467-023-36559-0","article-title":"Single-cell biological network inference using a heterogeneous graph transformer","volume":"14","author":"Ma","year":"2023","journal-title":"Nat. Commun."},{"issue":"1","key":"10.1016\/j.neucom.2026.134432_bib0055","doi-asserted-by":"crossref","first-page":"6601","DOI":"10.1038\/s41467-024-50955-0","article-title":"Accurate prediction of protein function using statistics-informed graph networks","volume":"15","author":"Jang","year":"2024","journal-title":"Nat. Commun."},{"issue":"8","key":"10.1016\/j.neucom.2026.134432_bib0060","doi-asserted-by":"crossref","first-page":"4549","DOI":"10.1007\/s10115-024-02097-4","article-title":"Deep graph clustering via mutual information maximization and mixture model","volume":"66","author":"Ahmadi","year":"2024","journal-title":"Knowl. Inf. Syst."},{"key":"10.1016\/j.neucom.2026.134432_bib0065","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"7603","article-title":"Deep graph clustering via dual correlation reduction","volume":"vol. 36","author":"Liu","year":"2022"},{"key":"10.1016\/j.neucom.2026.134432_bib0070","author":"V. d. Oord"},{"key":"10.1016\/j.neucom.2026.134432_bib0075","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"8914","article-title":"Hard sample aware network for contrastive deep graph clustering","volume":"vol. 37","author":"Liu","year":"2023"},{"issue":"4","key":"10.1016\/j.neucom.2026.134432_bib0080","doi-asserted-by":"crossref","first-page":"5858","DOI":"10.1109\/TNNLS.2024.3403155","article-title":"Deep clustering: a comprehensive survey","volume":"36","author":"Ren","year":"2024","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"10","key":"10.1016\/j.neucom.2026.134432_bib0085","doi-asserted-by":"crossref","first-page":"13789","DOI":"10.1109\/TNNLS.2023.3271871","article-title":"Simple contrastive graph clustering","volume":"35","author":"Liu","year":"2023","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.neucom.2026.134432_bib0090","series-title":"IJCAI","first-page":"3434","article-title":"Graph debiased contrastive learning with joint representation clustering","author":"Zhao","year":"2021"},{"key":"10.1016\/j.neucom.2026.134432_bib0095","doi-asserted-by":"crossref","first-page":"52884","DOI":"10.52202\/075280-2301","article-title":"Harnessing hard mixed samples with decoupled regularizer","volume":"36","author":"Liu","year":"2023","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.134432_bib0100","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2024.112672","article-title":"From overfitting to robustness: quantity, quality, and variety oriented negative sample selection in graph contrastive learning","volume":"170","author":"Ali","year":"2025","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.neucom.2026.134432_bib0105","series-title":"IJCAI","first-page":"2300","article-title":"CuCo: graph representation with curriculum contrastive learning","author":"Chu","year":"2021"},{"key":"10.1016\/j.neucom.2026.134432_bib0110","doi-asserted-by":"crossref","DOI":"10.1016\/j.chaos.2025.116921","article-title":"A bilevel-optimization-driven evolutionary algorithm for community detection in multilayer networks with significant topological differences","volume":"200","author":"Gao","year":"2025","journal-title":"Chaos Solit. Fractals"},{"key":"10.1016\/j.neucom.2026.134432_bib0115","series-title":"Evolutionary Computation and Complex Networks","author":"Liu","year":"2019"},{"issue":"10","key":"10.1016\/j.neucom.2026.134432_bib0120","doi-asserted-by":"crossref","first-page":"18020","DOI":"10.1109\/TNNLS.2025.3587020","article-title":"A self-supervised heterogeneous graph attention model based on adaptable step-size metapaths","volume":"36","author":"Teng","year":"2025","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10.1016\/j.neucom.2026.134432_bib0125","series-title":"International Conference on Machine Learning","first-page":"478","article-title":"Unsupervised deep embedding for clustering analysis","author":"Xie","year":"2016"},{"key":"10.1016\/j.neucom.2026.134432_bib0130","article-title":"Deep subspace clustering networks","volume":"30","author":"Ji","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.neucom.2026.134432_bib0135","series-title":"IJCAI","first-page":"1753","article-title":"Improved deep embedded clustering with local structure preservation","volume":"vol. 17","author":"Guo","year":"2017"},{"key":"10.1016\/j.neucom.2026.134432_bib0140","author":"Dilokthanakul"},{"key":"10.1016\/j.neucom.2026.134432_bib0145","author":"Kipf"},{"key":"10.1016\/j.neucom.2026.134432_bib0150","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"9978","article-title":"Deep fusion clustering network","volume":"vol. 35","author":"Tu","year":"2021"},{"issue":"5","key":"10.1016\/j.neucom.2026.134432_bib0155","doi-asserted-by":"crossref","first-page":"855","DOI":"10.26599\/TST.2021.9010066","article-title":"Graph convolutional network combined with semantic feature guidance for deep clustering","volume":"27","author":"Chen","year":"2022","journal-title":"Tsinghua Sci. Technol."},{"key":"10.1016\/j.neucom.2026.134432_bib0160","author":"Veli\u010dkovi\u0107"},{"key":"10.1016\/j.neucom.2026.134432_bib0165","series-title":"Proceedings of the 2023 15th International Conference on Machine Learning and Computing","first-page":"368","article-title":"Deep attributed graph clustering with graph attention network","author":"Zhu","year":"2023"},{"key":"10.1016\/j.neucom.2026.134432_bib0170","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.122182","article-title":"Deep dual graph attention auto-encoder for community detection","volume":"238","author":"Wu","year":"2024","journal-title":"Expert Syst. Appl."},{"issue":"2","key":"10.1016\/j.neucom.2026.134432_bib0175","doi-asserted-by":"crossref","first-page":"1336","DOI":"10.1007\/s10489-022-03381-y","article-title":"Deep graph clustering with enhanced feature representations for community detection","volume":"53","author":"Hao","year":"2023","journal-title":"Appl. Intell."},{"key":"10.1016\/j.neucom.2026.134432_bib0180","doi-asserted-by":"crossref","DOI":"10.1016\/j.iot.2025.101651","article-title":"DSEAGC: dual-spectral embedding for attributed graph clustering","volume":"32","author":"Zhao","year":"2025","journal-title":"Internet Things"},{"issue":"6","key":"10.1016\/j.neucom.2026.134432_bib0185","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1007\/s00530-025-01998-w","article-title":"A new method for attributed graph clustering with dual-manifold orthogonal matrix learning: T. yu, s. Nejadshamsi","volume":"31","author":"Yu","year":"2025","journal-title":"Multimed. Syst."},{"issue":"9","key":"10.1016\/j.neucom.2026.134432_bib0190","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3765742","article-title":"Relative entropy-based regularized non-negative matrix factorization for attributed graph clustering","volume":"19","author":"Berahmand","year":"2025","journal-title":"ACM Trans. Knowl. Discov. Data"},{"issue":"9","key":"10.1016\/j.neucom.2026.134432_bib0195","first-page":"4591","article-title":"Adaptive neighborhood metric learning","volume":"44","author":"Song","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.neucom.2026.134432_bib0200","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"6398","article-title":"Circle loss: a unified perspective of pair similarity optimization","author":"Sun","year":"2020"},{"issue":"6","key":"10.1016\/j.neucom.2026.134432_bib0205","doi-asserted-by":"crossref","first-page":"366","DOI":"10.1007\/s00530-024-01567-7","article-title":"Contrastive graph clustering via enhanced hard sample mining and cluster-guiding","volume":"30","author":"Li","year":"2024","journal-title":"Multimed. Syst."},{"issue":"3","key":"10.1016\/j.neucom.2026.134432_bib0210","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2024.104050","article-title":"Contrastive deep graph clustering with hard boundary sample awareness","volume":"62","author":"Zhu","year":"2025","journal-title":"Inf. Process. Manag."},{"issue":"4","key":"10.1016\/j.neucom.2026.134432_bib0215","doi-asserted-by":"crossref","DOI":"10.1016\/j.ipm.2025.104084","article-title":"MHGC: multi-scale hard sample mining for contrastive deep graph clustering","volume":"62","author":"Ren","year":"2025","journal-title":"Inf. Process. Manag."},{"key":"10.1016\/j.neucom.2026.134432_bib0220","series-title":"International Conference on Machine Learning","first-page":"4116","article-title":"Contrastive multi-view representation learning on graphs","author":"Hassani","year":"2020"},{"key":"10.1016\/j.neucom.2026.134432_bib0225","series-title":"Proceedings of the 31st ACM International Conference on Multimedia","first-page":"319","article-title":"CONVERT: contrastive graph clustering with reliable augmentation","author":"Yang","year":"2023"},{"key":"10.1016\/j.neucom.2026.134432_bib0230","series-title":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","first-page":"1968","article-title":"Revisiting modularity maximization for graph clustering: a contrastive learning perspective","author":"Liu","year":"2024"},{"key":"10.1016\/j.neucom.2026.134432_bib0235","series-title":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","first-page":"1341","article-title":"HomoGCL: rethinking homophily in graph contrastive learning","author":"Li","year":"2023"},{"key":"10.1016\/j.neucom.2026.134432_bib0240","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"van der L","year":"2008","journal-title":"J. Mach. Learn. Res."},{"key":"10.1016\/j.neucom.2026.134432_bib0245","series-title":"The World Wide Web Conference","first-page":"2022","article-title":"Heterogeneous graph attention network","author":"Wang","year":"2019"}],"container-title":["Neurocomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226018308?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231226018308?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T19:34:46Z","timestamp":1784057686000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0925231226018308"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":49,"alternative-id":["S0925231226018308"],"URL":"https:\/\/doi.org\/10.1016\/j.neucom.2026.134432","relation":{},"ISSN":["0925-2312"],"issn-type":[{"value":"0925-2312","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"MASCN: Multi-view attribute-structure consistency network for contrastive deep graph clustering","name":"articletitle","label":"Article Title"},{"value":"Neurocomputing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neucom.2026.134432","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"134432"}}