{"id":"https://openalex.org/W4415493090","doi":"https://doi.org/10.1007/s11063-025-11785-3","title":"Multi-view Fusion and View-specific-labels Learning for Multi-label Classification","display_name":"Multi-view Fusion and View-specific-labels Learning for Multi-label Classification","publication_year":2025,"publication_date":"2025-10-24","ids":{"openalex":"https://openalex.org/W4415493090","doi":"https://doi.org/10.1007/s11063-025-11785-3"},"language":"en","primary_location":{"id":"doi:10.1007/s11063-025-11785-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-025-11785-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-025-11785-3.pdf","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://link.springer.com/content/pdf/10.1007/s11063-025-11785-3.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049753764","display_name":"Zhengrong Yang","orcid":"https://orcid.org/0000-0001-9284-5593"},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhongliu Yang","raw_affiliation_strings":["College of Information Engineering, Shanghai Maritime University, Shanghai 201306, Shanghai, People\u2019s Republic of China"],"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shanghai Maritime University, Shanghai 201306, Shanghai, People\u2019s Republic of China","institution_ids":["https://openalex.org/I96733725"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040628447","display_name":"Jun Yin","orcid":"https://orcid.org/0000-0002-9085-3925"},"institutions":[{"id":"https://openalex.org/I96733725","display_name":"Shanghai Maritime University","ror":"https://ror.org/04z7qrj66","country_code":"CN","type":"education","lineage":["https://openalex.org/I96733725"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Yin","raw_affiliation_strings":["College of Information Engineering, Shanghai Maritime University, Shanghai 201306, Shanghai, People\u2019s Republic of China"],"affiliations":[{"raw_affiliation_string":"College of Information Engineering, Shanghai Maritime University, Shanghai 201306, Shanghai, People\u2019s Republic of China","institution_ids":["https://openalex.org/I96733725"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5049753764"],"corresponding_institution_ids":["https://openalex.org/I96733725"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15794026,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"57","issue":"6","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9998000264167786,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9998000264167786,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9817000031471252,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9735999703407288,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6092000007629395},{"id":"https://openalex.org/keywords/computational-intelligence","display_name":"Computational intelligence","score":0.5863000154495239},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5557000041007996},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5432999730110168},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5404000282287598},{"id":"https://openalex.org/keywords/fraction","display_name":"Fraction (chemistry)","score":0.4977000057697296},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.3982999920845032}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7289999723434448},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6543999910354614},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6092000007629395},{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.5863000154495239},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5557000041007996},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5525000095367432},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5432999730110168},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5404000282287598},{"id":"https://openalex.org/C149629883","wikidata":"https://www.wikidata.org/wiki/Q660926","display_name":"Fraction (chemistry)","level":2,"score":0.4977000057697296},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.3982999920845032},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.3799999952316284},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37709999084472656},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3650999963283539},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.3458000123500824},{"id":"https://openalex.org/C2982962833","wikidata":"https://www.wikidata.org/wiki/Q17092450","display_name":"Information fusion","level":2,"score":0.3409999907016754},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.296999990940094},{"id":"https://openalex.org/C164752517","wikidata":"https://www.wikidata.org/wiki/Q5570875","display_name":"Global optimization","level":2,"score":0.27959999442100525},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.26499998569488525}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s11063-025-11785-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-025-11785-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-025-11785-3.pdf","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/s11063-025-11785-3","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-025-11785-3","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-025-11785-3.pdf","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":[],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5740701018","display_name":null,"funder_award_id":"62476166","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","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":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4415493090.pdf"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W1201875361","https://openalex.org/W1515340688","https://openalex.org/W1969954882","https://openalex.org/W1981613567","https://openalex.org/W1999954155","https://openalex.org/W2052684427","https://openalex.org/W2090630554","https://openalex.org/W2114315281","https://openalex.org/W2156935079","https://openalex.org/W2166912588","https://openalex.org/W2176228818","https://openalex.org/W2296034168","https://openalex.org/W2605997098","https://openalex.org/W2736682637","https://openalex.org/W2782155089","https://openalex.org/W2794084401","https://openalex.org/W2808239701","https://openalex.org/W2881233020","https://openalex.org/W2892816441","https://openalex.org/W2896318470","https://openalex.org/W2903903916","https://openalex.org/W2906168345","https://openalex.org/W2929376427","https://openalex.org/W2938834426","https://openalex.org/W2963680343","https://openalex.org/W2964281107","https://openalex.org/W2980604334","https://openalex.org/W2981337591","https://openalex.org/W2990720125","https://openalex.org/W3034782107","https://openalex.org/W3126817395","https://openalex.org/W3169047433","https://openalex.org/W3184322403","https://openalex.org/W4213347131","https://openalex.org/W4281852995","https://openalex.org/W4312290604","https://openalex.org/W4382468418"],"related_works":[],"abstract_inverted_index":{"In":[0,175],"multi-view":[1,136,142,181],"multi-label":[2,104,146,182],"learning,":[3],"each":[4,32,50],"sample":[5],"is":[6,164],"characterized":[7],"by":[8],"multiple":[9,15,47],"views":[10,25],"and":[11,49,88,109,153,157],"simultaneously":[12,154],"labeled":[13],"with":[14,133],"semantic":[16],"labels.":[17,39],"Previous":[18],"approaches":[19,65],"typically":[20],"combined":[21],"information":[22,124],"from":[23],"various":[24,127],"to":[26,102,121,138,166,169,191],"obtain":[27],"a":[28,35,55,99,140],"shared":[29,36,119,123],"subspace,":[30],"assuming":[31],"view":[33,51],"has":[34],"set":[37],"of":[38,46,57],"However,":[40],"these":[41,95],"methods":[42],"ignore":[43],"the":[44,58,63,118,126,134,184],"diversity":[45],"views,":[48],"can":[52],"only":[53],"capture":[54,122],"fraction":[56],"complete":[59],"label":[60,74,81,159],"space.":[61],"Moreover,":[62],"current":[64],"in":[66],"this":[67],"field":[68],"often":[69],"rely":[70],"on":[71,179],"either":[72],"global":[73,87,156],"structures":[75],"or":[76],"local":[77,89,158],"smoothness":[78],"for":[79],"learning":[80],"correlations,":[82],"disregarding":[83],"scenarios":[84],"where":[85],"both":[86],"correlations":[90],"are":[91],"crucial.":[92],"To":[93,144],"tackle":[94],"issues,":[96],"we":[97,115,130,149],"present":[98],"new":[100,141],"method":[101,186],"improve":[103],"classification":[105,147],"through":[106],"Multi-view":[107],"Fusion":[108],"View-specific-labels":[110],"Learning":[111],"(MFVL).":[112],"More":[113],"concretely,":[114],"first":[116],"get":[117],"subspace":[120],"across":[125],"views.":[128],"Next,":[129],"combine":[131],"it":[132],"original":[135],"dataset":[137],"construct":[139],"dataset.":[143],"enhance":[145],"performance,":[148],"learn":[150],"view-specific":[151],"labels":[152],"consider":[155],"correlations.":[160],"Finally,":[161],"our":[162],"model":[163],"extended":[165],"nonlinear":[167],"version":[168],"effectively":[170],"handle":[171],"linearly":[172],"inseparable":[173],"problem.":[174],"numerous":[176],"experiments":[177],"conducted":[178],"nine":[180],"datasets,":[183],"proposed":[185],"achieves":[187],"superior":[188],"performance":[189],"compared":[190],"state-of-the-art":[192],"algorithms.":[193]},"counts_by_year":[],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-24T00:00:00"}