{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T13:21:12Z","timestamp":1777987272175,"version":"3.51.4"},"reference-count":38,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100004001","name":"Guizhou Provincial Science and Technology Department","doi-asserted-by":"publisher","award":["QKHCG-DXGA[2025]-ZD002"],"award-info":[{"award-number":["QKHCG-DXGA[2025]-ZD002"]}],"id":[{"id":"10.13039\/501100004001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002701","name":"Ministry of Education","doi-asserted-by":"publisher","award":["WZG-202506"],"award-info":[{"award-number":["WZG-202506"]}],"id":[{"id":"10.13039\/501100002701","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62262005"],"award-info":[{"award-number":["62262005"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010828","name":"Department of Education of Guizhou Province","doi-asserted-by":"publisher","award":["QJJ[2023]011"],"award-info":[{"award-number":["QJJ[2023]011"]}],"id":[{"id":"10.13039\/501100010828","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100017325","name":"Engineering Research Centers","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100017325","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Expert Systems with Applications"],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1016\/j.eswa.2026.132348","type":"journal-article","created":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T15:16:59Z","timestamp":1775315819000},"page":"132348","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Attribute-decoupled graph neural architecture search for discrete point anomaly detection"],"prefix":"10.1016","volume":"322","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3005-4064","authenticated-orcid":false,"given":"Jiamin","family":"Chen","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0326-3693","authenticated-orcid":false,"given":"Zhenpeng","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Tairan","family":"Huang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0006-1254-3434","authenticated-orcid":false,"given":"Xinqiu","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0002-4528-7220","authenticated-orcid":false,"given":"Siyang","family":"Xiao","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5241-7703","authenticated-orcid":false,"given":"Weihua","family":"Ou","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.eswa.2026.132348_bib0001","first-page":"1","article-title":"Variational autoencoder based anomaly detection using reconstruction probability","volume":"2","author":"An","year":"2015","journal-title":"Special Lecture on IE"},{"key":"10.1016\/j.eswa.2026.132348_bib0002","series-title":"Proceedings of European conference on principles of data mining and knowledge discovery (PKDD)","first-page":"15","article-title":"Fast outlier detection in high dimensional spaces","author":"Angiulli","year":"2002"},{"key":"10.1016\/j.eswa.2026.132348_bib0003","first-page":"281","article-title":"Random search for hyper-parameter optimization","volume":"13","author":"Bergstra","year":"2012","journal-title":"Journal of Machine Learning Research"},{"key":"10.1016\/j.eswa.2026.132348_bib0004","first-page":"3496","article-title":"Graph neural networks with convolutional arma filters","volume":"44","author":"Bianchi","year":"2021","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"10.1016\/j.eswa.2026.132348_bib0005","series-title":"Proceedings of the ACM SIGMOD international conference on management of data (SIGMOD)","first-page":"93","article-title":"LOF: Identifying density-based local outliers","author":"Breunig","year":"2000"},{"key":"10.1016\/j.eswa.2026.132348_bib0006","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TCIAIG.2012.2186810","article-title":"A survey of Monte Carlo tree search methods","volume":"4","author":"Browne","year":"2012","journal-title":"IEEE Transactions on Computational Intelligence and AI in games"},{"key":"10.1016\/j.eswa.2026.132348_bib0007","series-title":"Proceedings of the international conference on machine learning (ICML)","first-page":"1","article-title":"Leveraging diffusion model as pseudo-anomalous graph generator for graph-level anomaly detection","author":"Cai","year":"2025"},{"key":"10.1016\/j.eswa.2026.132348_bib0008","doi-asserted-by":"crossref","first-page":"3117","DOI":"10.1109\/TPDS.2022.3151895","article-title":"Auto-GNAS: A parallel graph neural architecture search framework","volume":"33","author":"Chen","year":"2022","journal-title":"IEEE Transactions on Parallel and Distributed Systems"},{"key":"10.1016\/j.eswa.2026.132348_bib0009","doi-asserted-by":"crossref","DOI":"10.1016\/j.ins.2024.120700","article-title":"Decoupled differentiable graph neural architecture search","volume":"673","author":"Chen","year":"2024","journal-title":"Information Sciences"},{"key":"10.1016\/j.eswa.2026.132348_bib0010","series-title":"Proceedings of the international conference on computers and games (ICCG)","first-page":"72","article-title":"Efficient selectivity and backup operators in monte-carlo tree search","volume":"vol. 4630","author":"Coulom","year":"2006"},{"key":"10.1016\/j.eswa.2026.132348_bib0011","doi-asserted-by":"crossref","DOI":"10.1016\/j.ins.2023.119617","article-title":"Search for deep graph neural networks","volume":"649","author":"Feng","year":"2023","journal-title":"Information Sciences"},{"key":"10.1016\/j.eswa.2026.132348_bib0012","series-title":"Proceedings of the conference on international joint conferences on artificial intelligence (IJCAI)","first-page":"1403","article-title":"Graph neural architecture search","author":"Gao","year":"2021"},{"key":"10.1016\/j.eswa.2026.132348_bib0013","series-title":"Proceedings of the AAAI conference on artificial intelligence (AAAI)","first-page":"6737","article-title":"LUNAR: Unifying local outlier detection methods via graph neural networks","author":"Goodge","year":"2022"},{"key":"10.1016\/j.eswa.2026.132348_bib0014","series-title":"Proceedings of the international conference on machine learning","first-page":"7968","article-title":"Large-scale graph neural architecture search","author":"Guan","year":"2022"},{"key":"10.1016\/j.eswa.2026.132348_bib0015","series-title":"Proceedings of the international conference on neural information processing systems (neurIPS)","first-page":"1025","article-title":"Inductive representation learning on large graphs","author":"Hamilton","year":"2017"},{"key":"10.1016\/j.eswa.2026.132348_bib0016","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.126667","article-title":"Graph-enhanced anomaly detection framework in multivariate time series using graph attention and enhanced generative adversarial networks","volume":"271","author":"He","year":"2025","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2026.132348_bib0017","series-title":"Proceedings of the international conference on learning representations (ICLR)","first-page":"1","article-title":"Semi-supervised classification with graph convolutional networks","author":"Kipf","year":"2017"},{"key":"10.1016\/j.eswa.2026.132348_bib0018","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.127379","article-title":"Uncertainty-informed dynamic threshold for time series anomaly detection","volume":"278","author":"Lee","year":"2025","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2026.132348_bib0019","series-title":"Proceedings of the international conference on learning representations (ICLR)","first-page":"1","article-title":"DiffGAD: A diffusion-based unsupervised graph anomaly detector","author":"Li","year":"2025"},{"key":"10.1016\/j.eswa.2026.132348_bib0020","series-title":"Proceedings of the ACM SIGKDD conference on knowledge discovery and data mining","first-page":"1458","article-title":"Causal-aware graph neural architecture search under distribution shifts","author":"Li","year":"2025"},{"key":"10.1016\/j.eswa.2026.132348_bib0021","series-title":"Proceedings of the international conference on neural information processing (ICONIP)","first-page":"189","article-title":"Autograph: Automated graph neural network","author":"Li","year":"2020"},{"key":"10.1016\/j.eswa.2026.132348_bib0022","series-title":"Proceedings of the IEEE international conference on data mining (ICDM)","first-page":"413","article-title":"Isolation forest","author":"Liu","year":"2008"},{"key":"10.1016\/j.eswa.2026.132348_bib0023","first-page":"1517","article-title":"Generative adversarial active learning for unsupervised outlier detection","volume":"32","author":"Liu","year":"2019","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"86","key":"10.1016\/j.eswa.2026.132348_bib0024","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"},{"key":"10.1016\/j.eswa.2026.132348_bib0025","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1023\/A:1013689704352","article-title":"Finite-time analysis of the multiarmed bandit problem","volume":"47","author":"Peter Auer","year":"2002","journal-title":"Machine Learning"},{"key":"10.1016\/j.eswa.2026.132348_bib0026","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (CVPR)","first-page":"2806","article-title":"Panda: Adapting pretrained features for anomaly detection and segmentation","author":"Reiss","year":"2021"},{"key":"10.1016\/j.eswa.2026.132348_bib0027","series-title":"Proceedings of the ACM international conference on web search and data mining (WSDM)","first-page":"576","article-title":"GAD-NR: Graph anomaly detection via neighborhood reconstruction","author":"Roy","year":"2024"},{"key":"10.1016\/j.eswa.2026.132348_bib0028","series-title":"Proceedings of the MLSDA workshop on machine learning for sensory data analysis (MLSDA)","first-page":"4","article-title":"Anomaly detection using autoencoders with nonlinear dimensionality reduction","author":"Sakurada","year":"2014"},{"key":"10.1016\/j.eswa.2026.132348_bib0029","doi-asserted-by":"crossref","first-page":"1443","DOI":"10.1162\/089976601750264965","article-title":"Estimating the support of a high-dimensional distribution","volume":"13","author":"Sch\u00f6lkopf","year":"2001","journal-title":"Neural Computation"},{"key":"10.1016\/j.eswa.2026.132348_bib0030","doi-asserted-by":"crossref","first-page":"484","DOI":"10.1038\/nature16961","article-title":"Mastering the game of go with deep neural networks and tree search","volume":"529","author":"Silver","year":"2016","journal-title":"Nature"},{"key":"10.1016\/j.eswa.2026.132348_bib0031","series-title":"Proceedings of the international conference on neural information processing systems (NeurIPS)","first-page":"29628","article-title":"Gadbench: Revisiting and benchmarking supervised graph anomaly detection","author":"Tang","year":"2023"},{"key":"10.1016\/j.eswa.2026.132348_bib0032","series-title":"Proceedings of the international conference on learning representations (ICLR)","first-page":"1","article-title":"Graph attention networks","author":"Velickovic","year":"2018"},{"key":"10.1016\/j.eswa.2026.132348_bib0033","doi-asserted-by":"crossref","first-page":"4155","DOI":"10.1109\/TETCI.2024.3386833","article-title":"Graph structure learning with automatic search of hyperparameters based on genetic programming","volume":"8","author":"Wang","year":"2024","journal-title":"IEEE Transactions on Emerging Topics in Computational Intelligence"},{"key":"10.1016\/j.eswa.2026.132348_bib0034","series-title":"Proceedings of the international conference on machine learning (ICML)","first-page":"6861","article-title":"Simplifying graph convolutional networks","author":"Wu","year":"2019"},{"key":"10.1016\/j.eswa.2026.132348_bib0035","series-title":"Proceedings of the international conference on learning representations (ICLR)","first-page":"1","article-title":"How powerful are graph neural networks?","author":"Xu","year":"2019"},{"key":"10.1016\/j.eswa.2026.132348_bib0036","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2025.127154","article-title":"MSTAgent-VAD: Multi-scale video anomaly detection using time agent mechanism for segments\u2019 temporal context mining","volume":"276","author":"Zhao","year":"2025","journal-title":"Expert Systems with Applications"},{"key":"10.1016\/j.eswa.2026.132348_bib0037","series-title":"Proceedings of the international conference on information and knowledge management","first-page":"4379","article-title":"FreeGAD: A training-free yet effective approach for graph anomaly detection","author":"Zhao","year":"2025"},{"key":"10.1016\/j.eswa.2026.132348_bib0038","series-title":"Proceedings of the international conference on learning representations (ICLR)","first-page":"1","article-title":"Deep autoencoding gaussian mixture model for unsupervised anomaly detection","author":"Zong","year":"2018"}],"container-title":["Expert Systems with Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426012613?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0957417426012613?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T12:29:50Z","timestamp":1777984190000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0957417426012613"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8]]},"references-count":38,"alternative-id":["S0957417426012613"],"URL":"https:\/\/doi.org\/10.1016\/j.eswa.2026.132348","relation":{},"ISSN":["0957-4174"],"issn-type":[{"value":"0957-4174","type":"print"}],"subject":[],"published":{"date-parts":[[2026,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Attribute-decoupled graph neural architecture search for discrete point anomaly detection","name":"articletitle","label":"Article Title"},{"value":"Expert Systems with Applications","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.eswa.2026.132348","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"132348"}}