{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T14:08:11Z","timestamp":1772114891719,"version":"3.50.1"},"reference-count":40,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2022,2,1]],"date-time":"2022-02-01T00:00:00Z","timestamp":1643673600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2022,2,1]],"date-time":"2022-02-01T00:00:00Z","timestamp":1643673600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2022,2,1]],"date-time":"2022-02-01T00:00:00Z","timestamp":1643673600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2022,2,1]],"date-time":"2022-02-01T00:00:00Z","timestamp":1643673600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2022,2,1]],"date-time":"2022-02-01T00:00:00Z","timestamp":1643673600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2022,2,1]],"date-time":"2022-02-01T00:00:00Z","timestamp":1643673600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,2,1]],"date-time":"2022-02-01T00:00:00Z","timestamp":1643673600000},"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":["61473150"],"award-info":[{"award-number":["61473150"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018YFC2001600"],"award-info":[{"award-number":["2018YFC2001600"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018YFC2001602"],"award-info":[{"award-number":["2018YFC2001602"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Pattern Recognition"],"published-print":{"date-parts":[[2022,2]]},"DOI":"10.1016\/j.patcog.2021.108334","type":"journal-article","created":{"date-parts":[[2021,9,21]],"date-time":"2021-09-21T23:22:36Z","timestamp":1632266556000},"page":"108334","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":75,"special_numbering":"C","title":["Graph Clustering via Variational Graph Embedding"],"prefix":"10.1016","volume":"122","author":[{"given":"Lin","family":"Guo","sequence":"first","affiliation":[]},{"given":"Qun","family":"Dai","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.patcog.2021.108334_bib0001","series-title":"the International Conference on Learning Representations","first-page":"40","article-title":"Revisiting semi-supervised learning with graph embeddings","author":"Yang","year":"2016"},{"key":"10.1016\/j.patcog.2021.108334_bib0002","series-title":"the International World Wide Web Conferences","first-page":"1271","article-title":"Explicit Semantic Ranking for Academic Search via Knowledge Graph Embedding","author":"Xiong","year":"2017"},{"key":"10.1016\/j.patcog.2021.108334_bib0003","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1007\/s13735-016-0102-y","article-title":"Learning content-social influential features for influence analysis","author":"Zhao","year":"2016","journal-title":"the International Journal of Multimedia Information Retrieval"},{"key":"10.1016\/j.patcog.2021.108334_bib0004","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/j.patcog.2018.11.007","article-title":"Auto-weighted multi-view clustering via kernelized graph learning","volume":"88","author":"Huang","year":"2019","journal-title":"Pattern Recognit"},{"key":"10.1016\/j.patcog.2021.108334_bib0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2019.107145","article-title":"Graph regularized low-rank representation for submodule clustering","volume":"100","author":"Wu","year":"2020","journal-title":"Pattern Recognit"},{"key":"10.1016\/j.patcog.2021.108334_bib0006","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.patcog.2017.06.012","article-title":"Discriminative metric learning for multi-view graph partitioning","volume":"75","author":"Li","year":"2018","journal-title":"Pattern Recognit"},{"key":"10.1016\/j.patcog.2021.108334_bib0007","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2019.06.014","article-title":"CutESC: Cutting edge spatial clustering technique based on proximity graphs","volume":"96","author":"Aksac","year":"2019","journal-title":"Pattern Recognit"},{"key":"10.1016\/j.patcog.2021.108334_bib0008","doi-asserted-by":"crossref","first-page":"2237","DOI":"10.1016\/j.patcog.2011.12.015","article-title":"Graph dual regularization non-negative matrix factorization for co-clustering","volume":"45","author":"Shang","year":"2012","journal-title":"Pattern Recognit"},{"key":"10.1016\/j.patcog.2021.108334_bib0009","first-page":"701","article-title":"DeepWalk: online learning of social representations","author":"Perozzi","year":"2014","journal-title":"ACM Knowledge Discovery and Data Mining"},{"key":"10.1016\/j.patcog.2021.108334_bib0010","series-title":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","first-page":"855","article-title":"node2vec: Scalable Feature Learning for Networks","author":"Grover","year":"2016"},{"key":"10.1016\/j.patcog.2021.108334_bib0011","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2020.107627","article-title":"Structured graph learning for clustering and semi-supervised classification","volume":"110","author":"Kang","year":"2021","journal-title":"Pattern Recognit"},{"key":"10.1016\/j.patcog.2021.108334_bib0012","series-title":"Annual Conference on Neural Information Processing Systems","first-page":"1024","article-title":"Inductive Representation Learning on Large Graphs","author":"Hamilton","year":"2017"},{"key":"10.1016\/j.patcog.2021.108334_bib0013","series-title":"the International Conference on Learning Representations","article-title":"Graph Attention Networks","author":"Veli\u010dkovi\u0107","year":"2018"},{"key":"10.1016\/j.patcog.2021.108334_bib0014","series-title":"the Annual Conference on Neural Information Processing Systems Workshop on Bayesian Deep Learning","article-title":"Variational Graph Auto-Encoders","author":"Kipf","year":"2016"},{"key":"10.1016\/j.patcog.2021.108334_bib0015","series-title":"Proceedings of the 2017 ACM on Conference on Information and Knowledge Management","first-page":"889","article-title":"Semi-Supervised Classification with Graph Convolutional Networks","author":"Kipf","year":"2017"},{"key":"10.1016\/j.patcog.2021.108334_bib0016","series-title":"Proceedings of the 2017 ACM on Conference on Information and Knowledge Management","first-page":"889","article-title":"MGAE: Marginalized Graph Autoencoder for Graph Clustering","author":"Wang","year":"2017"},{"key":"10.1016\/j.patcog.2021.108334_bib0017","series-title":"the International Joint Conference on Artificial Intelligence","first-page":"2609","article-title":"Adversarially Regularized Graph Autoencoder for Graph Embedding","author":"Pan","year":"2018"},{"key":"10.1016\/j.patcog.2021.108334_bib0018","first-page":"161727","article-title":"A Deep Graph Structured Clustering Network","volume":"8","author":"Xunkai","year":"2020","journal-title":"IEEEAccess"},{"key":"10.1016\/j.patcog.2021.108334_bib0019","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2018\/4867304","article-title":"Variational Approach for Learning Community Structures","volume":"2018","author":"Choong","year":"2018","journal-title":"Complexity"},{"key":"10.1016\/j.patcog.2021.108334_bib0020","series-title":"Annual Conference on Neural Information Processing Systems","first-page":"10712","article-title":"Semi-implicit graph variational auto-encoders","author":"Hasanzadeh","year":"2019"},{"key":"10.1016\/j.patcog.2021.108334_bib0021","doi-asserted-by":"crossref","unstructured":"Di Jin, Zhizhi Yu, Pengfei Jiao, Shirui Pan, Philip S. Yu and Weixiong Zhang, A Survey of Community Detection Approaches:From Statistical Modeling to Deep Learning, arXiv: 2101.01669v1, (2021).","DOI":"10.1109\/TKDE.2021.3104155"},{"key":"10.1016\/j.patcog.2021.108334_bib0022","unstructured":"Yaochen Xie, Zhao Xu, Zhengyang Wang, Shuiwang Ji, Self-Supervised Learning of Graph Neural Networks: A Unified Review, arXiv: 2102.10757v2, (2021)."},{"key":"10.1016\/j.patcog.2021.108334_bib0023","series-title":"the International Conference on Learning Representations","first-page":"478","article-title":"Unsupervised deep embedding for clustering analysis","author":"Xie","year":"2016"},{"key":"10.1016\/j.patcog.2021.108334_bib0024","doi-asserted-by":"crossref","first-page":"2323","DOI":"10.1126\/science.290.5500.2323","article-title":"Nonlinear Dimensionality Reduction by Locally Linear Embedding","volume":"290","author":"Roweis","year":"2000","journal-title":"Science"},{"key":"10.1016\/j.patcog.2021.108334_bib0025","series-title":"Annual Conference on Neural Information Processing Systems","first-page":"585","article-title":"Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering","author":"Belkin","year":"2001"},{"key":"10.1016\/j.patcog.2021.108334_bib0026","series-title":"the Pacific Rim International Conference on Artificial Intelligence","first-page":"1293","article-title":"Learning deep representations for graph clustering","author":"Tian","year":"2014"},{"key":"10.1016\/j.patcog.2021.108334_bib0027","series-title":"the International World Wide Web Conferences","first-page":"37","article-title":"Distributed large-scale natural graph factorization","author":"Ahmed","year":"2013"},{"key":"10.1016\/j.patcog.2021.108334_bib0028","series-title":"the Pacific Rim International Conference on Artificial Intelligence","first-page":"1145","article-title":"Deep neural networks for learning graph representations","author":"Cao","year":"2015"},{"key":"10.1016\/j.patcog.2021.108334_bib0029","series-title":"the International Conference on Artificial Intelligence and Statistics","first-page":"81","article-title":"Relational Topic Models for Document Networks","author":"Chang","year":"2009"},{"key":"10.1016\/j.patcog.2021.108334_bib0030","series-title":"the Pacific Rim International Conference on Artificial Intelligence","first-page":"2149","article-title":"Robust multi-view spectral clustering via low-rank and sparse decomposition","author":"Xia","year":"2014"},{"key":"10.1016\/j.patcog.2021.108334_bib0031","series-title":"the Pacific Rim International Conference on Artificial Intelligence","first-page":"2111","article-title":"Network representation learning with rich text information","author":"Yang","year":"2015"},{"key":"10.1016\/j.patcog.2021.108334_bib0032","series-title":"Annual Conference on Neural Information Processing Systems","first-page":"3844","article-title":"Convolutional neural networks on graphs with fast localized spectral filtering","author":"Defferrard","year":"2016"},{"key":"10.1016\/j.patcog.2021.108334_bib0033","series-title":"the International Conference on Learning Representations","article-title":"Auto-Encoding Variational Bayes","author":"Kingma","year":"2014"},{"key":"10.1016\/j.patcog.2021.108334_bib0034","series-title":"International Conference on Tools with Artificial Intelligence","first-page":"989","article-title":"Graph Attention Auto-Encoders","author":"Salehi","year":"2020"},{"key":"10.1016\/j.patcog.2021.108334_bib0035","unstructured":"Keting Cen, Huawei Shen, Jinhua Gao, Qi Cao, Bingbing Xu, Xueqi Cheng, ANAE: Learning Node Context Representation for Attributed Network Embedding, arXiv: 1906.08745v3, 2019."},{"key":"10.1016\/j.patcog.2021.108334_bib0036","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1016\/j.acha.2010.04.005","article-title":"Wavelets on graphs via spectral graph theory","volume":"30","author":"Hammond","year":"2011","journal-title":"Applied and Computational Harmonic Analysis"},{"key":"10.1016\/j.patcog.2021.108334_bib0037","series-title":"Proceedings of the 18th conference on Winter simulation","first-page":"260","article-title":"Sample-based non-uniform random variate generation","author":"Devroye","year":"1986"},{"key":"10.1016\/j.patcog.2021.108334_bib0038","series-title":"Annual Conference on Neural Information Processing Systems","article-title":"Dirichlet graph variational autoencoder","author":"Li","year":"2020"},{"key":"10.1016\/j.patcog.2021.108334_bib0039","series-title":"the International Conference on Learning Representations","article-title":"Adam: A Method for Stochastic Optimization","author":"Kingma","year":"2015"},{"key":"10.1016\/j.patcog.2021.108334_bib0040","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Van Der Maaten","year":"2008","journal-title":"Journal of Machine Learning Research"}],"container-title":["Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320321005148?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320321005148?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,9,21]],"date-time":"2025-09-21T17:06:41Z","timestamp":1758474401000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0031320321005148"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2]]},"references-count":40,"alternative-id":["S0031320321005148"],"URL":"https:\/\/doi.org\/10.1016\/j.patcog.2021.108334","relation":{},"ISSN":["0031-3203"],"issn-type":[{"value":"0031-3203","type":"print"}],"subject":[],"published":{"date-parts":[[2022,2]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Graph Clustering via Variational Graph Embedding","name":"articletitle","label":"Article Title"},{"value":"Pattern Recognition","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.patcog.2021.108334","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2021 Elsevier Ltd. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"108334"}}