{"id":"https://openalex.org/W4401051988","doi":"https://doi.org/10.1007/s40747-024-01562-5","title":"Incomplete multi-view partial multi-label classification via deep semantic structure preservation","display_name":"Incomplete multi-view partial multi-label classification via deep semantic structure preservation","publication_year":2024,"publication_date":"2024-07-27","ids":{"openalex":"https://openalex.org/W4401051988","doi":"https://doi.org/10.1007/s40747-024-01562-5"},"language":"en","primary_location":{"id":"doi:10.1007/s40747-024-01562-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40747-024-01562-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40747-024-01562-5.pdf","source":{"id":"https://openalex.org/S3035462843","display_name":"Complex & Intelligent Systems","issn_l":"2198-6053","issn":["2198-6053","2199-4536"],"is_oa":true,"is_in_doaj":true,"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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complex & Intelligent Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s40747-024-01562-5.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006173142","display_name":"Chaoran Li","orcid":"https://orcid.org/0000-0001-9118-5386"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chaoran Li","raw_affiliation_strings":["College of Big Data and Information Engineering, Guizhou University, Guiyang, China"],"affiliations":[{"raw_affiliation_string":"College of Big Data and Information Engineering, Guizhou University, Guiyang, China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063066514","display_name":"Xiyin Wu","orcid":"https://orcid.org/0000-0002-4456-9691"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiyin Wu","raw_affiliation_strings":["College of Big Data and Information Engineering, Guizhou University, Guiyang, China"],"affiliations":[{"raw_affiliation_string":"College of Big Data and Information Engineering, Guizhou University, Guiyang, China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103110081","display_name":"Pai Peng","orcid":"https://orcid.org/0000-0002-7129-6174"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pai Peng","raw_affiliation_strings":["College of Big Data and Information Engineering, Guizhou University, Guiyang, China"],"affiliations":[{"raw_affiliation_string":"College of Big Data and Information Engineering, Guizhou University, Guiyang, China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055084263","display_name":"Zhuhong Zhang","orcid":"https://orcid.org/0000-0001-9093-5691"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuhong Zhang","raw_affiliation_strings":["College of Big Data and Information Engineering, Guizhou University, Guiyang, China"],"affiliations":[{"raw_affiliation_string":"College of Big Data and Information Engineering, Guizhou University, Guiyang, China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001365689","display_name":"Xiaohuan Lu","orcid":"https://orcid.org/0009-0006-7634-7272"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohuan Lu","raw_affiliation_strings":["College of Big Data and Information Engineering, Guizhou University, Guiyang, China"],"affiliations":[{"raw_affiliation_string":"College of Big Data and Information Engineering, Guizhou University, Guiyang, China","institution_ids":["https://openalex.org/I178232147"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5006173142"],"corresponding_institution_ids":["https://openalex.org/I178232147"],"apc_list":{"value":1320,"currency":"GBP","value_usd":1619},"apc_paid":{"value":1320,"currency":"GBP","value_usd":1619},"fwci":2.5067,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.90559499,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"10","issue":"6","first_page":"7661","last_page":"7679"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9997000098228455,"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":0.9997000098228455,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9891999959945679,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9851999878883362,"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/computer-science","display_name":"Computer science","score":0.7747959494590759},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5501469373703003},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5394464731216431},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5084289908409119},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.47579631209373474},{"id":"https://openalex.org/keywords/semantic-feature","display_name":"Semantic feature","score":0.47015929222106934},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46411827206611633},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.435698002576828},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4341597557067871},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4317648112773895},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4310375154018402},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.42042112350463867},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.40893495082855225},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37447744607925415},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1177598237991333}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7747959494590759},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5501469373703003},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5394464731216431},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5084289908409119},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.47579631209373474},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.47015929222106934},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46411827206611633},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.435698002576828},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4341597557067871},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4317648112773895},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4310375154018402},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.42042112350463867},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.40893495082855225},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37447744607925415},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1177598237991333},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s40747-024-01562-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40747-024-01562-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40747-024-01562-5.pdf","source":{"id":"https://openalex.org/S3035462843","display_name":"Complex & Intelligent Systems","issn_l":"2198-6053","issn":["2198-6053","2199-4536"],"is_oa":true,"is_in_doaj":true,"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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complex & Intelligent Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:59c70df38d084a1cbd954baf8c4302f9","is_oa":true,"landing_page_url":"https://doaj.org/article/59c70df38d084a1cbd954baf8c4302f9","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Complex & Intelligent Systems, Vol 10, Iss 6, Pp 7661-7679 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s40747-024-01562-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40747-024-01562-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40747-024-01562-5.pdf","source":{"id":"https://openalex.org/S3035462843","display_name":"Complex & Intelligent Systems","issn_l":"2198-6053","issn":["2198-6053","2199-4536"],"is_oa":true,"is_in_doaj":true,"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","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complex & Intelligent Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1426168230","display_name":null,"funder_award_id":"62063002","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":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4401051988.pdf"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1937059634","https://openalex.org/W1981613567","https://openalex.org/W2019899889","https://openalex.org/W2031489346","https://openalex.org/W2090630554","https://openalex.org/W2096166399","https://openalex.org/W2114315281","https://openalex.org/W2127719807","https://openalex.org/W2129144539","https://openalex.org/W2129906471","https://openalex.org/W2141282920","https://openalex.org/W2428757121","https://openalex.org/W2590019597","https://openalex.org/W2787932447","https://openalex.org/W2808239701","https://openalex.org/W2899051391","https://openalex.org/W2907382309","https://openalex.org/W2938834426","https://openalex.org/W2962724911","https://openalex.org/W2966027244","https://openalex.org/W3007788930","https://openalex.org/W3094527485","https://openalex.org/W3118550943","https://openalex.org/W3126817395","https://openalex.org/W3169047433","https://openalex.org/W3196105425","https://openalex.org/W3209420330","https://openalex.org/W4319300038","https://openalex.org/W4361801401","https://openalex.org/W4385451016","https://openalex.org/W4387493034","https://openalex.org/W4391360925","https://openalex.org/W4392303344","https://openalex.org/W6600674394"],"related_works":["https://openalex.org/W2381850946","https://openalex.org/W4380449851","https://openalex.org/W3125091513","https://openalex.org/W4318832338","https://openalex.org/W1919390113","https://openalex.org/W4248383205","https://openalex.org/W4234745530","https://openalex.org/W4309346246","https://openalex.org/W4311555960","https://openalex.org/W4390871823"],"abstract_inverted_index":{"Abstract":[0],"Recent":[1],"advances":[2],"in":[3,21,27],"multi-view":[4],"multi-label":[5],"learning":[6,111,136],"are":[7],"often":[8],"hampered":[9],"by":[10],"the":[11,36,39,44,66,116,122,130,141,148,153,173,194,212],"prevalent":[12],"challenges":[13,34],"of":[14,38,48,68,118,144,156,175,214],"incomplete":[15,100],"views":[16,101],"and":[17,30,102,169,183,207,217],"missing":[18,103,145],"labels,":[19,146],"common":[20],"real-world":[22],"data":[23,28,215],"due":[24],"to":[25,41,54,79,114,139,171],"uncertainties":[26],"collection":[29],"manual":[31],"annotation.":[32],"These":[33],"restrict":[35],"capacity":[37],"model":[40,95,160],"fully":[42],"utilize":[43],"diverse":[45],"semantic":[46,69,81,92,119,176,219],"information":[47,178],"each":[49],"sample,":[50],"posing":[51],"significant":[52],"barriers":[53],"effective":[55],"learning.":[56],"Despite":[57],"substantial":[58],"scholarly":[59],"efforts,":[60],"many":[61],"existing":[62,198],"methods":[63],"inadequately":[64],"capture":[65],"depth":[67],"information,":[70],"focusing":[71],"primarily":[72],"on":[73],"shallow":[74],"feature":[75,123,181],"extractions":[76],"that":[77,96,165,193],"fail":[78],"maintain":[80,172],"consistency.":[82],"To":[83],"address":[84,140],"these":[85],"shortcomings,":[86],"we":[87],"propose":[88],"a":[89,108,133,162],"novel":[90],"Deep":[91],"structure-preserving":[93],"(SSP)":[94],"effectively":[97,210],"tackles":[98],"both":[99,180],"labels.":[104],"SSP":[105,131,159,195],"innovatively":[106],"incorporates":[107],"graph":[109],"constraint":[110],"(GCL)":[112],"scheme":[113],"ensure":[115],"preservation":[117],"structure":[120,155],"throughout":[121],"extraction":[124,182],"process":[125],"across":[126,188],"different":[127],"views.":[128],"Additionally,":[129],"integrates":[132],"pseudo-labeling":[134],"self-paced":[135],"(PSL)":[137],"strategy":[138],"often-overlooked":[142],"issue":[143],"enhancing":[147],"classification":[149,184],"accuracy":[150],"while":[151],"preserving":[152],"distribution":[154],"data.":[157],"The":[158],"creates":[161],"unified":[163],"framework":[164],"synergistically":[166],"employs":[167],"GCL":[168],"PSL":[170],"integrity":[174],"structural":[177],"during":[179],"phases.":[185],"Extensive":[186],"evaluations":[187],"five":[189],"real":[190],"datasets":[191],"demonstrate":[192],"method":[196],"outperforms":[197],"approaches,":[199],"including":[200],"lrMMC,":[201],"MVL-IV,":[202],"MvEL,":[203],"iMSF,":[204],"iMvWL,":[205],"NAIML,":[206],"DD-IMvMLC-net.":[208],"It":[209],"mitigates":[211],"impacts":[213],"incompleteness":[216],"enhances":[218],"representation":[220],"fidelity.":[221]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":4}],"updated_date":"2026-03-17T17:19:04.345684","created_date":"2025-10-10T00:00:00"}