{"id":"https://openalex.org/W7153500376","doi":"https://doi.org/10.1007/s11063-026-11848-z","title":"ECMVC: Entropy-aware Curriculum-guided Multi-view Contrastive Clustering","display_name":"ECMVC: Entropy-aware Curriculum-guided Multi-view Contrastive Clustering","publication_year":2026,"publication_date":"2026-04-11","ids":{"openalex":"https://openalex.org/W7153500376","doi":"https://doi.org/10.1007/s11063-026-11848-z"},"language":"en","primary_location":{"id":"doi:10.1007/s11063-026-11848-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-026-11848-z","pdf_url":null,"source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1007/s11063-026-11848-z","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133066678","display_name":"Jun Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I124644866","display_name":"Northwest Minzu University","ror":"https://ror.org/04cyy9943","country_code":"CN","type":"education","lineage":["https://openalex.org/I124644866"]},{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jun Ma","raw_affiliation_strings":["School of National Languages Information Technology, Northwest Minzu University, Lanzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of National Languages Information Technology, Northwest Minzu University, Lanzhou, China","institution_ids":["https://openalex.org/I124644866","https://openalex.org/I145897649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5118741588","display_name":"Yuquan Shao","orcid":null},"institutions":[{"id":"https://openalex.org/I124644866","display_name":"Northwest Minzu University","ror":"https://ror.org/04cyy9943","country_code":"CN","type":"education","lineage":["https://openalex.org/I124644866"]},{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuquan Shao","raw_affiliation_strings":["School of National Languages Information Technology, Northwest Minzu University, Lanzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of National Languages Information Technology, Northwest Minzu University, Lanzhou, China","institution_ids":["https://openalex.org/I124644866","https://openalex.org/I145897649"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133404500","display_name":"Yangyang Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I179026463","display_name":"Beijing Technology and Business University","ror":"https://ror.org/013e0zm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I179026463"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yangyang Zhou","raw_affiliation_strings":["School of Information Technology, Beijing Technology and Business University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Technology, Beijing Technology and Business University, Beijing, China","institution_ids":["https://openalex.org/I179026463"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5133419517","display_name":"Wenjing Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I124644866","display_name":"Northwest Minzu University","ror":"https://ror.org/04cyy9943","country_code":"CN","type":"education","lineage":["https://openalex.org/I124644866"]},{"id":"https://openalex.org/I145897649","display_name":"Minzu University of China","ror":"https://ror.org/0044e2g62","country_code":"CN","type":"education","lineage":["https://openalex.org/I145897649"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjing Jia","raw_affiliation_strings":["School of National Languages Information Technology, Northwest Minzu University, Lanzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of National Languages Information Technology, Northwest Minzu University, Lanzhou, China","institution_ids":["https://openalex.org/I124644866","https://openalex.org/I145897649"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5133066678"],"corresponding_institution_ids":["https://openalex.org/I124644866","https://openalex.org/I145897649"],"apc_list":{"value":2990,"currency":"USD","value_usd":2990},"apc_paid":{"value":2990,"currency":"USD","value_usd":2990},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.44303064,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"58","issue":"3","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.29170000553131104,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.29170000553131104,"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/T10057","display_name":"Face and Expression Recognition","score":0.14910000562667847,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.07270000129938126,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7621999979019165},{"id":"https://openalex.org/keywords/computational-intelligence","display_name":"Computational intelligence","score":0.5115000009536743},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.44600000977516174},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.43309998512268066},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.3903999924659729},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3741999864578247},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.3702000081539154},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.3619999885559082},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.35190001130104065}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7642999887466431},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7621999979019165},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6291000247001648},{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.5115000009536743},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4964999854564667},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.44859999418258667},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.44600000977516174},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.43309998512268066},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3903999924659729},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3741999864578247},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.3702000081539154},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.3619999885559082},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.35190001130104065},{"id":"https://openalex.org/C202269582","wikidata":"https://www.wikidata.org/wiki/Q2644277","display_name":"Complementarity (molecular biology)","level":2,"score":0.3497999906539917},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3481000065803528},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.3292999863624573},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.32339999079704285},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3163999915122986},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3077999949455261},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.30410000681877136},{"id":"https://openalex.org/C39235581","wikidata":"https://www.wikidata.org/wiki/Q5158434","display_name":"Conceptual clustering","level":5,"score":0.29440000653266907},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.2865000069141388},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C27964816","wikidata":"https://www.wikidata.org/wiki/Q5164359","display_name":"Constrained clustering","level":5,"score":0.26570001244544983},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.2597000002861023},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.2535000145435333},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.25220000743865967},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s11063-026-11848-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-026-11848-z","pdf_url":null,"source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s11063-026-11848-z","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-026-11848-z","pdf_url":null,"source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7256268858909607}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1722318740","https://openalex.org/W2093102386","https://openalex.org/W2110455444","https://openalex.org/W2532039214","https://openalex.org/W2809368372","https://openalex.org/W2827746458","https://openalex.org/W2899512866","https://openalex.org/W2900681603","https://openalex.org/W2921065608","https://openalex.org/W2996771119","https://openalex.org/W3024865103","https://openalex.org/W3035524453","https://openalex.org/W3102111485","https://openalex.org/W3136208589","https://openalex.org/W3200387849","https://openalex.org/W3209810427","https://openalex.org/W3215043003","https://openalex.org/W4304098891","https://openalex.org/W4309835919","https://openalex.org/W4312973985","https://openalex.org/W4313413477","https://openalex.org/W4386071520","https://openalex.org/W4387968141","https://openalex.org/W4390873400","https://openalex.org/W4394862694","https://openalex.org/W4399385905","https://openalex.org/W4401024520","https://openalex.org/W4401729983","https://openalex.org/W4402652631","https://openalex.org/W4402776594","https://openalex.org/W4407574141","https://openalex.org/W4408355987","https://openalex.org/W4409154664","https://openalex.org/W4409917197","https://openalex.org/W4409982245"],"related_works":[],"abstract_inverted_index":{"Multi-view":[0],"clustering":[1,44,86,114],"aims":[2],"to":[3,10,63,107],"integrate":[4],"complementary":[5],"information":[6,81],"from":[7],"multiple":[8,158],"views":[9,31,100],"achieve":[11],"better":[12],"performance":[13],"than":[14],"single-view":[15],"clustering.":[16],"However,":[17],"in":[18,115],"practical":[19],"scenarios,":[20],"the":[21,42,109,143,162,165],"quality":[22],"of":[23,113,164],"each":[24],"view":[25],"is":[26],"often":[27],"inconsistent,":[28],"with":[29],"some":[30],"containing":[32],"substantial":[33],"noise":[34],"or":[35],"redundant":[36,118],"information,":[37],"which":[38],"may":[39],"adversely":[40],"affect":[41],"overall":[43],"performance.":[45],"Moreover,":[46],"existing":[47],"contrastive":[48,85,127],"learning":[49,128],"techniques":[50],"typically":[51],"employ":[52],"overly":[53],"simplistic":[54],"strategies":[55],"for":[56],"negative":[57,138],"sample":[58],"selection,":[59],"making":[60],"them":[61],"prone":[62],"local":[64],"optima":[65],"during":[66],"training":[67,144],"and":[68,97,101,111,117,140,152],"compromising":[69],"model":[70],"effectiveness.":[71],"To":[72],"address":[73],"these":[74],"challenges,":[75],"this":[76],"paper":[77],"proposes":[78],"a":[79,103,125],"novel":[80],"fusion-based":[82],"deep":[83],"multi-view":[84],"algorithm,":[87],"termed":[88],"ECMVC.":[89],"The":[90],"proposed":[91,166],"method":[92],"explicitly":[93],"models":[94],"both":[95],"consistency":[96],"complementarity":[98],"among":[99],"leverages":[102],"feature":[104],"fusion":[105],"network":[106],"enhance":[108],"stability":[110],"accuracy":[112],"noisy":[116],"environments.":[119],"In":[120],"addition,":[121],"we":[122],"further":[123],"propose":[124],"curriculum-guided":[126,147],"approach,":[129],"where":[130],"an":[131],"entropy-driven":[132],"dynamic":[133],"scheduler":[134],"adaptively":[135],"selects":[136],"informative":[137],"samples":[139],"progressively":[141],"increases":[142],"difficulty.":[145],"This":[146],"mechanism":[148],"enables":[149],"faster":[150],"convergence":[151],"more":[153],"stable":[154],"optimization.":[155],"Experiments":[156],"on":[157],"benchmark":[159],"datasets":[160],"demonstrate":[161],"effectiveness":[163],"method.":[167]},"counts_by_year":[],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2026-04-12T00:00:00"}