{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,16]],"date-time":"2024-09-16T07:16:47Z","timestamp":1726471007671},"reference-count":49,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Engineering Applications of Artificial Intelligence"],"published-print":{"date-parts":[[2024,10]]},"DOI":"10.1016\/j.engappai.2024.108976","type":"journal-article","created":{"date-parts":[[2024,7,13]],"date-time":"2024-07-13T10:55:03Z","timestamp":1720868103000},"page":"108976","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"PA","title":["Towards a semi-supervised ensemble clustering framework with flexible weighting mechanism and constraints information"],"prefix":"10.1016","volume":"136","author":[{"given":"Jing","family":"Tang","sequence":"first","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0009-0003-3877-2276","authenticated-orcid":false,"given":"Decheng","family":"Xu","sequence":"additional","affiliation":[]},{"ORCID":"http:\/\/orcid.org\/0009-0000-2867-7660","authenticated-orcid":false,"given":"Qingwei","family":"Cai","sequence":"additional","affiliation":[]},{"given":"Shunlei","family":"Li","sequence":"additional","affiliation":[]},{"given":"Amin","family":"Rezaeipanah","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.engappai.2024.108976_bib1","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.118886","article-title":"Event stream controllability on event-based complex networks","volume":"213","author":"Arebi","year":"2023","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.engappai.2024.108976_bib2","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/j.csda.2016.08.003","article-title":"A simple approach to sparse clustering","volume":"105","author":"Arias-Castro","year":"2017","journal-title":"Comput. Stat. Data Anal."},{"issue":"8","key":"10.1016\/j.engappai.2024.108976_bib4","doi-asserted-by":"crossref","first-page":"1541","DOI":"10.2166\/wst.2020.220","article-title":"Application of unsupervised learning and process simulation for energy optimization of a WWTP under various weather conditions","volume":"81","author":"Borzooei","year":"2020","journal-title":"Water Sci. Technol."},{"issue":"D1","key":"10.1016\/j.engappai.2024.108976_bib5","doi-asserted-by":"crossref","first-page":"D1123","DOI":"10.1093\/nar\/gkab957","article-title":"webTWAS: a resource for disease candidate susceptibility genes identified by transcriptome-wide association study","volume":"50","author":"Cao","year":"2022","journal-title":"Nucleic Acids Res."},{"key":"10.1016\/j.engappai.2024.108976_bib6","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2022.109282","article-title":"Self-supervised semi-supervised nonnegative matrix factorization for data clustering","volume":"137","author":"Chavoshinejad","year":"2023","journal-title":"Pattern Recogn."},{"key":"10.1016\/j.engappai.2024.108976_bib7","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2024.108215","article-title":"A survey on semi-supervised graph clustering","volume":"133","author":"Daneshfar","year":"2024","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"16","key":"10.1016\/j.engappai.2024.108976_bib8","doi-asserted-by":"crossref","first-page":"12505","DOI":"10.1109\/JIOT.2020.3019398","article-title":"FraudTrip: taxi fraudulent trip detection from corresponding trajectories","volume":"8","author":"Ding","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"10.1016\/j.engappai.2024.108976_bib9","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2023.168814","article-title":"Physics-informed neural networks as surrogate models of hydrodynamic simulators","volume":"912","author":"Donnelly","year":"2024","journal-title":"Sci. Total Environ."},{"key":"10.1016\/j.engappai.2024.108976_bib10","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2023.107536","article-title":"Forecasting global climate drivers using Gaussian processes and convolutional autoencoders","volume":"128","author":"Donnelly","year":"2024","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.engappai.2024.108976_bib11","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.118751","article-title":"Adaptive safety-aware semi-supervised clustering","volume":"212","author":"Gan","year":"2023","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.engappai.2024.108976_bib12","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.future.2024.05.006","article-title":"Multi-task federated learning-based system anomaly detection and multi-classification for microservices architecture","volume":"159","author":"Hao","year":"2024","journal-title":"Future Generat. Comput. Syst."},{"issue":"1","key":"10.1016\/j.engappai.2024.108976_bib13","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1186\/s13677-024-00677-x","article-title":"Efficiently localizing system anomalies for cloud infrastructures: a novel Dynamic Graph Transformer based Parallel Framework","volume":"13","author":"He","year":"2024","journal-title":"J. Cloud Comput."},{"key":"10.1016\/j.engappai.2024.108976_bib14","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.engappai.2016.02.002","article-title":"Deep feature weighting for naive Bayes and its application to text classification","volume":"52","author":"Jiang","year":"2016","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"5","key":"10.1016\/j.engappai.2024.108976_bib16","first-page":"1481","article-title":"Semi-supervised three-way clustering ensemble based on seeds set and pairwise constraints","volume":"43","author":"Jiang","year":"2023","journal-title":"J. Comput. Appl."},{"key":"10.1016\/j.engappai.2024.108976_bib17","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.119733","article-title":"A semi-supervised resampling method for class-imbalanced learning","volume":"221","author":"Jiang","year":"2023","journal-title":"Expert Syst. Appl."},{"issue":"3","key":"10.1016\/j.engappai.2024.108976_bib18","doi-asserted-by":"crossref","first-page":"3064","DOI":"10.1109\/TIE.2023.3269463","article-title":"Electrical Fault diagnosis from text data: a supervised sentence embedding combined with imbalanced classification","volume":"71","author":"Jing","year":"2024","journal-title":"IEEE Trans. Ind. Electron."},{"issue":"10","key":"10.1016\/j.engappai.2024.108976_bib19","doi-asserted-by":"crossref","first-page":"7841","DOI":"10.1016\/j.jksuci.2022.07.003","article-title":"A novel self-directed learning framework for cluster ensemble","volume":"34","author":"Kadhim","year":"2022","journal-title":"Journal of King Saud University-Computer and Information Sciences"},{"key":"10.1016\/j.engappai.2024.108976_bib20","first-page":"II","article-title":"Multiobjective data clustering","volume":"2","author":"Law","year":"2004"},{"issue":"11","key":"10.1016\/j.engappai.2024.108976_bib21","doi-asserted-by":"crossref","first-page":"1398","DOI":"10.1111\/mice.12674","article-title":"Cross\u2010scene pavement distress detection by a novel transfer learning framework","volume":"36","author":"Li","year":"2021","journal-title":"Comput. Aided Civ. Infrastruct. Eng."},{"key":"10.1016\/j.engappai.2024.108976_bib22","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2022.119273","article-title":"A novel semi-supervised classification approach for evolving data streams","volume":"215","author":"Liao","year":"2023","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.engappai.2024.108976_bib23","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2024.110237","article-title":"An analysis of performance, pricing, and coordination in a supply chain with cloud services: the impact of data security","volume":"192","author":"Liu","year":"2024","journal-title":"Comput. Ind. Eng."},{"issue":"3","key":"10.1016\/j.engappai.2024.108976_bib24","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1007\/s11263-012-0602-z","article-title":"Exhaustive and efficient constraint propagation: a graph-based learning approach and its applications","volume":"103","author":"Lu","year":"2013","journal-title":"Int. J. Comput. Vis."},{"key":"10.1016\/j.engappai.2024.108976_bib25","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2024.108196","article-title":"Semi-supervised nonnegative matrix factorization with label propagation and constraint propagation","volume":"133","author":"Mo","year":"2024","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"8","key":"10.1016\/j.engappai.2024.108976_bib26","doi-asserted-by":"crossref","first-page":"1238","DOI":"10.1080\/0951192X.2023.2165160","article-title":"Manufacturing cost estimation based on similarity","volume":"36","author":"Ning","year":"2023","journal-title":"Int. J. Comput. Integrated Manuf."},{"key":"10.1016\/j.engappai.2024.108976_bib27","doi-asserted-by":"crossref","DOI":"10.1016\/j.ins.2023.119203","article-title":"Semi-supervised classifier ensemble model for high-dimensional data","volume":"643","author":"Niu","year":"2023","journal-title":"Inf. Sci."},{"issue":"1","key":"10.1016\/j.engappai.2024.108976_bib28","doi-asserted-by":"crossref","first-page":"39","DOI":"10.61186\/jsdp.20.1.39","article-title":"Ensembling semi-supervised p-spectral clustering for high dimensional data","volume":"20","author":"Safari","year":"2023","journal-title":"Signal and Data Processing"},{"issue":"12","key":"10.1016\/j.engappai.2024.108976_bib29","first-page":"3595","article-title":"PAC-bayesian analysis of Co-clustering and beyond","volume":"11","author":"Seldin","year":"2010","journal-title":"J. Mach. Learn. Res."},{"issue":"7","key":"10.1016\/j.engappai.2024.108976_bib30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3645087","article-title":"An all-inclusive taxonomy and critical review of blockchain-assisted authentication and session key generation protocols for IoT","volume":"56","author":"Shahidinejad","year":"2024","journal-title":"ACM Comput. Surv."},{"key":"10.1016\/j.engappai.2024.108976_bib31","doi-asserted-by":"crossref","DOI":"10.1016\/j.engappai.2023.106571","article-title":"Semi-supervised hierarchical ensemble clustering based on an innovative distance metric and constraint information","volume":"124","author":"Shen","year":"2023","journal-title":"Eng. Appl. Artif. Intell."},{"key":"10.1016\/j.engappai.2024.108976_bib32","doi-asserted-by":"crossref","DOI":"10.1016\/j.is.2023.102178","article-title":"Semi-supervised and un-supervised clustering: a review and experimental evaluation","volume":"114","author":"Taha","year":"2023","journal-title":"Inf. Syst."},{"issue":"2","key":"10.1016\/j.engappai.2024.108976_bib51","doi-asserted-by":"crossref","first-page":"919","DOI":"10.1007\/s10586-020-03152-9","article-title":"An efficient power-aware VM allocation mechanism in cloud data centers: a micro genetic-based approach","volume":"24","author":"Tarahomi","year":"2021","journal-title":"Cluster Comput."},{"key":"10.1016\/j.engappai.2024.108976_bib33","doi-asserted-by":"crossref","DOI":"10.1016\/j.artint.2020.103237","article-title":"Swarm intelligence for self-organized clustering","volume":"290","author":"Thrun","year":"2021","journal-title":"Artif. Intell."},{"issue":"2","key":"10.1016\/j.engappai.2024.108976_bib34","doi-asserted-by":"crossref","first-page":"668","DOI":"10.1109\/TGCN.2023.3249208","article-title":"A centralized control-based clustering scheme for energy efficiency in underwater acoustic sensor networks","volume":"7","author":"Tian","year":"2023","journal-title":"IEEE Transactions on Green Communications and Networking"},{"issue":"24","key":"10.1016\/j.engappai.2024.108976_bib35","doi-asserted-by":"crossref","first-page":"15811","DOI":"10.1021\/acs.analchem.9b04115","article-title":"Unconventional split aptamers cleaved at functionally essential sites preserve biorecognition capability","volume":"91","author":"Wang","year":"2019","journal-title":"Anal. Chem."},{"key":"10.1016\/j.engappai.2024.108976_bib36","doi-asserted-by":"crossref","first-page":"5257","DOI":"10.1109\/TIP.2022.3192706","article-title":"Extendable multiple nodes recurrent tracking framework with RTU++","volume":"31","author":"Wang","year":"2022","journal-title":"IEEE Trans. Image Process."},{"issue":"12","key":"10.1016\/j.engappai.2024.108976_bib52","first-page":"2257","article-title":"An ensemble CPU load prediction algorithm using a Bayesian information criterion and smooth filters in a cloud computing environment","volume":"48","author":"Tofighy","year":"2018","journal-title":"Software: Practice and Experience"},{"key":"10.1016\/j.engappai.2024.108976_bib37","doi-asserted-by":"crossref","DOI":"10.1016\/j.ins.2023.118994","article-title":"Pairwise constraints-based semi-supervised fuzzy clustering with multi-manifold regularization","volume":"638","author":"Wang","year":"2023","journal-title":"Inf. Sci."},{"key":"10.1016\/j.engappai.2024.108976_bib38","doi-asserted-by":"crossref","first-page":"98596","DOI":"10.1109\/ACCESS.2023.3313602","article-title":"Soft-label for multi-domain fake news detection","volume":"11","author":"Wang","year":"2023","journal-title":"IEEE Access"},{"issue":"6","key":"10.1016\/j.engappai.2024.108976_bib39","doi-asserted-by":"crossref","first-page":"188","DOI":"10.3390\/systems12060188","article-title":"Stacked noise reduction auto encoder\u2013OCEAN: a novel personalized recommendation model enhanced","volume":"12","author":"Wang","year":"2024","journal-title":"Systems"},{"key":"10.1016\/j.engappai.2024.108976_bib40","doi-asserted-by":"crossref","DOI":"10.1287\/isre.2022.0047","article-title":"Are neighbors alike? A semisupervised probabilistic collaborative learning model for online review spammers detection","author":"Wu","year":"2023","journal-title":"Inf. Syst. Res."},{"issue":"7","key":"10.1016\/j.engappai.2024.108976_bib41","doi-asserted-by":"crossref","first-page":"1230","DOI":"10.3390\/electronics13071230","article-title":"Lightweight privacy protection via adversarial sample","volume":"13","author":"Xie","year":"2024","journal-title":"Electronics"},{"key":"10.1016\/j.engappai.2024.108976_bib42","doi-asserted-by":"crossref","DOI":"10.1016\/j.cie.2022.108835","article-title":"Dynamic pickup and delivery problem with transshipments and LIFO constraints","volume":"175","author":"Xu","year":"2023","journal-title":"Comput. Ind. Eng."},{"key":"10.1016\/j.engappai.2024.108976_bib43","first-page":"509","article-title":"Subspace metric ensembles for semi-supervised clustering of high dimensional data","volume":"17","author":"Yan","year":"2006"},{"key":"10.1016\/j.engappai.2024.108976_bib45","doi-asserted-by":"crossref","unstructured":"Yin, L., Wang, L., Lu, S., Wang, R., Ren, H., AlSanad, A., et al. AFBNet: a lightweight adaptive feature fusion module for super-resolution algorithms. Comput. Model. Eng. Sci. DOI: 10.32604\/cmes.2024.050853.","DOI":"10.32604\/cmes.2024.050853"},{"issue":"8","key":"10.1016\/j.engappai.2024.108976_bib46","doi-asserted-by":"crossref","first-page":"1577","DOI":"10.1109\/TKDE.2017.2695615","article-title":"Adaptive ensembling of semi-supervised clustering solutions","volume":"29","author":"Yu","year":"2017","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"5","key":"10.1016\/j.engappai.2024.108976_bib47","doi-asserted-by":"crossref","first-page":"473","DOI":"10.2174\/1574893617666220404145517","article-title":"Distance-based support vector machine to predict DNA N6-methyladenine modification","volume":"17","author":"Zhang","year":"2022","journal-title":"Curr. Bioinf."},{"issue":"2","key":"10.1016\/j.engappai.2024.108976_bib48","doi-asserted-by":"crossref","first-page":"567","DOI":"10.1007\/s13042-022-01651-2","article-title":"Two-stage semi-supervised clustering ensemble framework based on constraint weight","volume":"14","author":"Zhang","year":"2023","journal-title":"International Journal of Machine Learning and Cybernetics"},{"key":"10.1016\/j.engappai.2024.108976_bib49","doi-asserted-by":"crossref","first-page":"29344","DOI":"10.1109\/ACCESS.2023.3260977","article-title":"Detection of android malware based on deep forest and feature enhancement","volume":"11","author":"Zhang","year":"2023","journal-title":"IEEE Access"},{"key":"10.1016\/j.engappai.2024.108976_bib50","doi-asserted-by":"crossref","DOI":"10.1016\/j.scs.2023.104718","article-title":"Multi-criteria evaluation and optimization of a novel thermodynamic cycle based on a wind farm, Kalina cycle and storage system: an effort to improve efficiency and sustainability","volume":"96","author":"Zhu","year":"2023","journal-title":"Sustain. Cities Soc."}],"container-title":["Engineering Applications of Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197624011345?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0952197624011345?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,8,29]],"date-time":"2024-08-29T06:42:41Z","timestamp":1724913761000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0952197624011345"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10]]},"references-count":49,"alternative-id":["S0952197624011345"],"URL":"https:\/\/doi.org\/10.1016\/j.engappai.2024.108976","relation":{},"ISSN":["0952-1976"],"issn-type":[{"type":"print","value":"0952-1976"}],"subject":[],"published":{"date-parts":[[2024,10]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Towards a semi-supervised ensemble clustering framework with flexible weighting mechanism and constraints information","name":"articletitle","label":"Article Title"},{"value":"Engineering Applications of Artificial Intelligence","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.engappai.2024.108976","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"108976"}}