{"id":"https://openalex.org/W4412488848","doi":"https://doi.org/10.1109/tnnls.2025.3586306","title":"Multilevel Reliable Guidance for Unpaired Multiview Clustering","display_name":"Multilevel Reliable Guidance for Unpaired Multiview Clustering","publication_year":2025,"publication_date":"2025-07-16","ids":{"openalex":"https://openalex.org/W4412488848","doi":"https://doi.org/10.1109/tnnls.2025.3586306","pmid":"https://pubmed.ncbi.nlm.nih.gov/40668704"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2025.3586306","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3586306","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/A5076978644","display_name":"Like Xin","orcid":"https://orcid.org/0000-0002-7516-4355"},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Like Xin","raw_affiliation_strings":["School of Mathematical Sciences, Nanjing Normal University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-7516-4355","affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, Nanjing Normal University, Nanjing, China","institution_ids":["https://openalex.org/I152031979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078658353","display_name":"Wanqi Yang","orcid":"https://orcid.org/0000-0001-6727-6077"},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanqi Yang","raw_affiliation_strings":["School of Computer and Electronic Information, Nanjing Normal University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-6727-6077","affiliations":[{"raw_affiliation_string":"School of Computer and Electronic Information, Nanjing Normal University, Nanjing, China","institution_ids":["https://openalex.org/I152031979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100435848","display_name":"Lei Wang","orcid":"https://orcid.org/0000-0002-0961-0441"},"institutions":[{"id":"https://openalex.org/I204824540","display_name":"University of Wollongong","ror":"https://ror.org/00jtmb277","country_code":"AU","type":"education","lineage":["https://openalex.org/I204824540"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Lei Wang","raw_affiliation_strings":["School of Computing and Information Technology, University of Wollongong, Wollongong, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0002-0961-0441","affiliations":[{"raw_affiliation_string":"School of Computing and Information Technology, University of Wollongong, Wollongong, NSW, Australia","institution_ids":["https://openalex.org/I204824540"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009256880","display_name":"Ming Yang","orcid":"https://orcid.org/0000-0002-8679-9137"},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Yang","raw_affiliation_strings":["School of Computer and Electronic Information, Nanjing Normal University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Electronic Information, Nanjing Normal University, Nanjing, China","institution_ids":["https://openalex.org/I152031979"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.4661,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.90157846,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"36","issue":"10","first_page":"18968","last_page":"18982"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9764999747276306,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9764999747276306,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.968999981880188,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9627000093460083,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8492375016212463},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.7503146529197693},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7117944955825806},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.5835475325584412},{"id":"https://openalex.org/keywords/hierarchical-clustering","display_name":"Hierarchical clustering","score":0.49901747703552246},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4667907655239105},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4654887914657593},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.43935805559158325},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35640639066696167}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8492375016212463},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.7503146529197693},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7117944955825806},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.5835475325584412},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.49901747703552246},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4667907655239105},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4654887914657593},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.43935805559158325},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35640639066696167},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2025.3586306","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3586306","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:40668704","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40668704","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/G1327198361","display_name":null,"funder_award_id":"62476136","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4459702006","display_name":null,"funder_award_id":"62276138","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":75,"referenced_works":["https://openalex.org/W1937059634","https://openalex.org/W1968855351","https://openalex.org/W1972441438","https://openalex.org/W2064608681","https://openalex.org/W2117079761","https://openalex.org/W2546561608","https://openalex.org/W2588822028","https://openalex.org/W2785810986","https://openalex.org/W2788790210","https://openalex.org/W2804016075","https://openalex.org/W2807776204","https://openalex.org/W2808465901","https://openalex.org/W2884826995","https://openalex.org/W2903938664","https://openalex.org/W2904900506","https://openalex.org/W2906529026","https://openalex.org/W2913724411","https://openalex.org/W2963433607","https://openalex.org/W2963517422","https://openalex.org/W2964199994","https://openalex.org/W2966632286","https://openalex.org/W2997864604","https://openalex.org/W3008209906","https://openalex.org/W3161727935","https://openalex.org/W3165208855","https://openalex.org/W3168316785","https://openalex.org/W3169978599","https://openalex.org/W3176728172","https://openalex.org/W3206460183","https://openalex.org/W3207532266","https://openalex.org/W4214544745","https://openalex.org/W4214642029","https://openalex.org/W4214876032","https://openalex.org/W4220898301","https://openalex.org/W4221166681","https://openalex.org/W4224926219","https://openalex.org/W4281679003","https://openalex.org/W4283806925","https://openalex.org/W4286896674","https://openalex.org/W4290927762","https://openalex.org/W4301347335","https://openalex.org/W4304091711","https://openalex.org/W4306913594","https://openalex.org/W4312238451","https://openalex.org/W4312881178","https://openalex.org/W4312946813","https://openalex.org/W4312973985","https://openalex.org/W4313066313","https://openalex.org/W4313576235","https://openalex.org/W4327937847","https://openalex.org/W4364302344","https://openalex.org/W4367016851","https://openalex.org/W4380520364","https://openalex.org/W4382202985","https://openalex.org/W4385420750","https://openalex.org/W4385489739","https://openalex.org/W4386075537","https://openalex.org/W4386932198","https://openalex.org/W4387381293","https://openalex.org/W4387450808","https://openalex.org/W4387968627","https://openalex.org/W4388101626","https://openalex.org/W4388692616","https://openalex.org/W4388953073","https://openalex.org/W4390873400","https://openalex.org/W4391365647","https://openalex.org/W4392745198","https://openalex.org/W4393147617","https://openalex.org/W4394015595","https://openalex.org/W4394951283","https://openalex.org/W4398226150","https://openalex.org/W4404101448","https://openalex.org/W4404300333","https://openalex.org/W4406259257","https://openalex.org/W4409362980"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W3200375535"],"abstract_inverted_index":{"In":[0],"this":[1,66],"article,":[2],"we":[3,89],"address":[4,65],"the":[5,50,54,82,132,166,193],"challenging":[6,80],"problem":[7],"of":[8,56,134,169,195,216],"unpaired":[9,21],"multiview":[10,29,219],"clustering":[11,19,30,103,122,167,199],"(UMC),":[12],"which":[13,100],"aims":[14],"to":[15,38,53,64,108,130,149,164,182],"achieve":[16,183],"effective":[17],"joint":[18],"using":[20],"samples":[22,37],"observed":[23],"across":[24,73,127,179],"multiple":[25,180],"views.":[26,43,172],"Traditional":[27],"incomplete":[28],"(IMC)":[31],"methods":[32],"typically":[33],"rely":[34],"on":[35,218],"paired":[36,57],"capture":[39],"complementary":[40],"information":[41],"between":[42],"However,":[44],"such":[45,77],"strategies":[46],"become":[47],"impractical":[48],"in":[49,138,197],"UMC":[51,98,209],"due":[52],"absence":[55],"samples.":[58],"Although":[59],"some":[60],"researchers":[61],"have":[62],"attempted":[63],"issue":[67],"by":[68],"preserving":[69],"consistent":[70,110,184],"cluster":[71,83,113,141,187],"structures":[72,84,114],"views,":[74],"effectively":[75],"mining":[76],"consistency":[78],"remains":[79],"when":[81],"with":[85],"low":[86],"confidence.":[87,200],"Therefore,":[88],"propose":[90],"a":[91,146,159],"novel":[92],"method,":[93],"multilevel":[94,102,121],"reliable":[95,105,160],"guidance":[96,107,157,162],"for":[97],"(MRG-UMC),":[99],"integrates":[101],"and":[104,111,153,185],"view":[106,120,148,161],"learn":[109],"confident":[112,140,186],"from":[115],"three":[116,174],"perspectives.":[117],"Specifically,":[118],"inner":[119],"exploits":[123],"high-confidence":[124],"sample":[125],"pairs":[126],"different":[128],"levels":[129,181],"reduce":[131],"impact":[133],"boundary":[135],"samples,":[136],"resulting":[137],"more":[139],"structures.":[142,188],"Synthesized-view":[143],"alignment":[144],"leverages":[145],"synthesized":[147],"mitigate":[150],"cross-view":[151],"discrepancies":[152],"promote":[154],"consistency.":[155],"Cross-view":[156],"employs":[158],"strategy":[163],"enhance":[165],"confidence":[168],"poorly":[170],"clustered":[171],"These":[173],"modules":[175],"are":[176],"jointly":[177],"optimized":[178],"Furthermore,":[189],"theoretical":[190],"analyses":[191],"verify":[192],"effectiveness":[194],"MRG-UMC":[196,206],"enhancing":[198],"Extensive":[201],"experimental":[202],"results":[203],"show":[204],"that":[205],"outperforms":[207],"state-of-the-art":[208],"methods,":[210],"achieving":[211],"an":[212],"average":[213],"NMI":[214],"improvement":[215],"12.95%":[217],"datasets.":[220],"The":[221],"source":[222],"code":[223],"is":[224],"available":[225],"at":[226],"https://anonymous.4open.science/r/MRG-UMC-5E20.":[227]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}