{"id":"https://openalex.org/W4386973885","doi":"https://doi.org/10.1109/tnnls.2023.3313692","title":"Iterative Deep Structural Graph Contrast Clustering for Multiview Raw Data","display_name":"Iterative Deep Structural Graph Contrast Clustering for Multiview Raw Data","publication_year":2023,"publication_date":"2023-09-22","ids":{"openalex":"https://openalex.org/W4386973885","doi":"https://doi.org/10.1109/tnnls.2023.3313692","pmid":"https://pubmed.ncbi.nlm.nih.gov/37738196"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3313692","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3313692","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009251223","display_name":"Zhibin Dong","orcid":"https://orcid.org/0000-0001-7829-4924"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhibin Dong","raw_affiliation_strings":["School of Computer, National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0001-7829-4924","affiliations":[{"raw_affiliation_string":"School of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101875008","display_name":"Jiaqi Jin","orcid":"https://orcid.org/0009-0000-0510-4472"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqi Jin","raw_affiliation_strings":["School of Computer, National University of Defense Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112896361","display_name":"Yuyang Xiao","orcid":"https://orcid.org/0009-0007-1727-3979"},"institutions":[{"id":"https://openalex.org/I56934997","display_name":"Changsha University of Science and Technology","ror":"https://ror.org/03yph8055","country_code":"CN","type":"education","lineage":["https://openalex.org/I56934997"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuyang Xiao","raw_affiliation_strings":["School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, China","institution_ids":["https://openalex.org/I56934997"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100656645","display_name":"Siwei Wang","orcid":"https://orcid.org/0000-0001-9517-262X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Siwei Wang","raw_affiliation_strings":["Intelligent Game and Decision Laboratory, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9517-262X","affiliations":[{"raw_affiliation_string":"Intelligent Game and Decision Laboratory, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100671239","display_name":"Xinzhong Zhu","orcid":"https://orcid.org/0000-0002-0033-5260"},"institutions":[{"id":"https://openalex.org/I135237710","display_name":"Zhejiang Normal University","ror":"https://ror.org/01vevwk45","country_code":"CN","type":"education","lineage":["https://openalex.org/I135237710"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinzhong Zhu","raw_affiliation_strings":["College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua, China"],"raw_orcid":"https://orcid.org/0000-0002-0033-5260","affiliations":[{"raw_affiliation_string":"College of Mathematics, Physics and Information Engineering, Zhejiang Normal University, Jinhua, China","institution_ids":["https://openalex.org/I135237710"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101727888","display_name":"Xinwang Liu","orcid":"https://orcid.org/0000-0001-9066-1475"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinwang Liu","raw_affiliation_strings":["School of Computer, National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0001-9066-1475","affiliations":[{"raw_affiliation_string":"School of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069681054","display_name":"En Zhu","orcid":"https://orcid.org/0000-0003-2305-7555"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"En Zhu","raw_affiliation_strings":["School of Computer, National University of Defense Technology, Changsha, China"],"raw_orcid":"https://orcid.org/0000-0003-2305-7555","affiliations":[{"raw_affiliation_string":"School of Computer, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4276,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.84683779,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"35","issue":"12","first_page":"18272","last_page":"18284"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9868999719619751,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9861999750137329,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7394062280654907},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7158792614936829},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5849615335464478},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5267861485481262},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4684109091758728},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4616604447364807},{"id":"https://openalex.org/keywords/clustering-coefficient","display_name":"Clustering coefficient","score":0.43994051218032837},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4219139516353607},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.4208952486515045},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4142787456512451},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3969312310218811}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7394062280654907},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7158792614936829},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5849615335464478},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5267861485481262},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4684109091758728},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4616604447364807},{"id":"https://openalex.org/C22047676","wikidata":"https://www.wikidata.org/wiki/Q898680","display_name":"Clustering coefficient","level":3,"score":0.43994051218032837},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4219139516353607},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.4208952486515045},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4142787456512451},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3969312310218811}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2023.3313692","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3313692","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:37738196","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37738196","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2455478723","display_name":null,"funder_award_id":"62276271","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3930773365","display_name":null,"funder_award_id":"62376279","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5729763073","display_name":null,"funder_award_id":"62325604","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6603744613","display_name":null,"funder_award_id":"62306324","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8378406381","display_name":null,"funder_award_id":"2022ZD0209103","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W1501500081","https://openalex.org/W1975172027","https://openalex.org/W1993962865","https://openalex.org/W1994615541","https://openalex.org/W1997201895","https://openalex.org/W2030209765","https://openalex.org/W2100495367","https://openalex.org/W2138621090","https://openalex.org/W2145072179","https://openalex.org/W2199534117","https://openalex.org/W2528578439","https://openalex.org/W2741943936","https://openalex.org/W2787885212","https://openalex.org/W2800791174","https://openalex.org/W2804847616","https://openalex.org/W2809299793","https://openalex.org/W2888654602","https://openalex.org/W2899604627","https://openalex.org/W2906217954","https://openalex.org/W2906424845","https://openalex.org/W2906529026","https://openalex.org/W2963764569","https://openalex.org/W2964015378","https://openalex.org/W2977506081","https://openalex.org/W2981206386","https://openalex.org/W2988613494","https://openalex.org/W2997739739","https://openalex.org/W3008739840","https://openalex.org/W3012918605","https://openalex.org/W3015507004","https://openalex.org/W3044096495","https://openalex.org/W3087124270","https://openalex.org/W3089039599","https://openalex.org/W3091192503","https://openalex.org/W3118054267","https://openalex.org/W3134487894","https://openalex.org/W3150746439","https://openalex.org/W3176947484","https://openalex.org/W3183553932","https://openalex.org/W3205512245","https://openalex.org/W3210338549","https://openalex.org/W3212924718","https://openalex.org/W3217558487","https://openalex.org/W4210518188","https://openalex.org/W4214536771","https://openalex.org/W4226080957","https://openalex.org/W4283792797","https://openalex.org/W4284965547","https://openalex.org/W4296913441","https://openalex.org/W4304091792","https://openalex.org/W4307501835","https://openalex.org/W4309363988","https://openalex.org/W4309364607","https://openalex.org/W4309364896","https://openalex.org/W4320713198","https://openalex.org/W4379382628","https://openalex.org/W4386075537","https://openalex.org/W6680922216","https://openalex.org/W6684578312","https://openalex.org/W6685357932","https://openalex.org/W6685380521","https://openalex.org/W6766091529","https://openalex.org/W6777265123","https://openalex.org/W6779518175","https://openalex.org/W6781695082","https://openalex.org/W6803318553"],"related_works":["https://openalex.org/W1999117613","https://openalex.org/W2040929534","https://openalex.org/W3022637481","https://openalex.org/W2393816671","https://openalex.org/W3120229345","https://openalex.org/W2111119584","https://openalex.org/W3144143113","https://openalex.org/W3039964395","https://openalex.org/W2804957450","https://openalex.org/W2357208913"],"abstract_inverted_index":{"Multiview":[0],"clustering":[1,28,85,256,280],"has":[2],"attracted":[3],"increasing":[4],"attention":[5],"to":[6,104,112,127,150,245,249],"automatically":[7],"divide":[8],"instances":[9],"into":[10],"various":[11],"groups":[12],"without":[13],"manual":[14],"annotations.":[15],"Traditional":[16],"shadow":[17],"methods":[18,168],"discover":[19],"the":[20,50,55,61,64,71,125,129,133,141,152,155,160,173,177,180,190,200,207,215,247,261,275],"internal":[21],"structure":[22,65,101,192],"of":[23,39,57,67,92,154,162,176,206],"data,":[24],"while":[25,60],"deep":[26,81,279],"multiview":[27,88,268],"(DMVC)":[29],"utilizes":[30],"neural":[31],"networks":[32],"with":[33,118],"clustering-friendly":[34,235],"data":[35,90],"embeddings.":[36],"Although":[37],"both":[38],"them":[40],"achieve":[41,105],"impressive":[42],"performance":[43],"in":[44,179],"practical":[45],"applications,":[46],"we":[47,74,185,238],"find":[48],"that":[49,271],"former":[51],"heavily":[52],"relies":[53],"on":[54,199,266],"quality":[56],"raw":[58,89,146],"features,":[59],"latter":[62],"ignores":[63],"information":[66,121],"data.":[68],"To":[69],"address":[70],"above":[72],"issue,":[73],"propose":[75],"a":[76,114,196,251],"novel":[77],"method":[78],"termed":[79],"iterative":[80,242,262],"structural":[82,120,130,143],"graph":[83,100,117,136,144,181,191],"contrast":[84],"(IDSGCC)":[86],"for":[87],"consisting":[91],"topology":[93,248],"learning":[94,97,103,171,183,188],"(TL),":[95],"representation":[96,174],"(RL),":[98],"and":[99,122,145,158,218,232,278],"contrastive":[102,170,182,187],"better":[106],"performance.":[107],"The":[108,203,226],"TL":[109],"module":[110],"aims":[111],"obtain":[113,234,250],"structured":[115],"global":[116,142],"constraint":[119],"then":[123],"guides":[124],"RL":[126,134],"preserve":[128],"information.":[131],"In":[132],"module,":[135,184],"convolutional":[137],"network":[138],"(GCN)":[139],"takes":[140],"features":[147],"as":[148,211,223],"inputs":[149],"aggregate":[151],"samples":[153,161,208,220],"same":[156],"cluster":[157],"keep":[159],"different":[163],"clusters":[164],"away.":[165],"Unlike":[166],"previous":[167],"performing":[169],"at":[172,189],"level":[175,193],"samples,":[178],"conduct":[186],"by":[194],"imposing":[195],"regularization":[197],"term":[198],"similarity":[201],"matrix.":[202],"credible":[204,216,253],"neighbors":[205],"are":[209,221,258],"constructed":[210,222],"positive":[212],"pairs":[213],"through":[214,260],"graph,":[217],"other":[219,231],"negative":[224],"pairs.":[225],"three":[227],"modules":[228],"promote":[229],"each":[230],"finally":[233],"embedding.":[236],"Also,":[237],"set":[239],"up":[240],"an":[241],"update":[243,246],"mechanism":[244],"more":[252],"topology.":[254],"Impressive":[255],"results":[257],"obtained":[259],"mechanism.":[263],"Comparative":[264],"experiments":[265],"eight":[267],"datasets":[269],"show":[270],"our":[272],"model":[273],"outperforms":[274],"state-of-the-art":[276],"traditional":[277],"competitors.":[281]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}