{"id":"https://openalex.org/W4395097378","doi":"https://doi.org/10.1109/tnnls.2024.3382911","title":"Multilabel Feature Selection via Shared Latent Sublabel Structure and Simultaneous Orthogonal Basis Clustering","display_name":"Multilabel Feature Selection via Shared Latent Sublabel Structure and Simultaneous Orthogonal Basis Clustering","publication_year":2024,"publication_date":"2024-04-24","ids":{"openalex":"https://openalex.org/W4395097378","doi":"https://doi.org/10.1109/tnnls.2024.3382911","pmid":"https://pubmed.ncbi.nlm.nih.gov/38656846"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2024.3382911","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3382911","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/A5054791684","display_name":"Ronghua Shang","orcid":"https://orcid.org/0000-0001-9124-696X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ronghua Shang","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi’an, Shaanxi, China"],"raw_orcid":"https://orcid.org/0000-0001-9124-696X","affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi’an, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009017652","display_name":"Jingyu Zhong","orcid":"https://orcid.org/0009-0006-8690-9419"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyu Zhong","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi’an, Shaanxi, China"],"raw_orcid":"https://orcid.org/0009-0006-8690-9419","affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi’an, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101735891","display_name":"Weitong Zhang","orcid":"https://orcid.org/0000-0003-1625-2870"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weitong Zhang","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi’an, Shaanxi, China"],"raw_orcid":"https://orcid.org/0000-0003-1625-2870","affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi’an, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046202286","display_name":"Songhua Xu","orcid":"https://orcid.org/0000-0002-2276-2538"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Songhua Xu","raw_affiliation_strings":["Department of Health Management and the Institute of Medical Artificial Intelligence, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Health Management and the Institute of Medical Artificial Intelligence, The Second Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100356496","display_name":"Yangyang Li","orcid":"https://orcid.org/0000-0002-1328-8889"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yangyang Li","raw_affiliation_strings":["Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi’an, Shaanxi, China"],"raw_orcid":"https://orcid.org/0000-0002-1328-8889","affiliations":[{"raw_affiliation_string":"Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education, School of Artificial Intelligence, Xidian University, Xi’an, Shaanxi, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.4809,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.98607004,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"36","issue":"3","first_page":"5288","last_page":"5303"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9998999834060669,"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":0.9998999834060669,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9882000088691711,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9850999712944031,"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":0.6567201614379883},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6184865832328796},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5177273154258728},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.49744799733161926},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48762407898902893},{"id":"https://openalex.org/keywords/probabilistic-latent-semantic-analysis","display_name":"Probabilistic latent semantic analysis","score":0.48390302062034607},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.43781834840774536}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6567201614379883},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6184865832328796},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5177273154258728},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49744799733161926},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48762407898902893},{"id":"https://openalex.org/C112933361","wikidata":"https://www.wikidata.org/wiki/Q2845258","display_name":"Probabilistic latent semantic analysis","level":2,"score":0.48390302062034607},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.43781834840774536},{"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:10.1109/tnnls.2024.3382911","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3382911","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:38656846","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/38656846","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/G1366720558","display_name":null,"funder_award_id":"2022JC-45","funder_id":"https://openalex.org/F4320336567","funder_display_name":"Natural Science Basic Research Program of Shaanxi Province"},{"id":"https://openalex.org/G2700949206","display_name":null,"funder_award_id":"62176200","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3559318170","display_name":null,"funder_award_id":"2021A1515110686","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G4919765520","display_name":null,"funder_award_id":"2022JQ-616","funder_id":"https://openalex.org/F4320336567","funder_display_name":"Natural Science Basic Research Program of Shaanxi Province"},{"id":"https://openalex.org/G5627121286","display_name":null,"funder_award_id":"12326617","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"},{"id":"https://openalex.org/F4320327912","display_name":"Higher Education Discipline Innovation Project","ror":null},{"id":"https://openalex.org/F4320336567","display_name":"Natural Science Basic Research Program of Shaanxi Province","ror":null},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W636917482","https://openalex.org/W1546847949","https://openalex.org/W1897044480","https://openalex.org/W1953606363","https://openalex.org/W2010262905","https://openalex.org/W2021661079","https://openalex.org/W2029517229","https://openalex.org/W2090630554","https://openalex.org/W2096086009","https://openalex.org/W2114315281","https://openalex.org/W2117553576","https://openalex.org/W2133510502","https://openalex.org/W2143854982","https://openalex.org/W2156935079","https://openalex.org/W2166912588","https://openalex.org/W2241072627","https://openalex.org/W2325261669","https://openalex.org/W2519969774","https://openalex.org/W2540382275","https://openalex.org/W2569112930","https://openalex.org/W2569859441","https://openalex.org/W2743621318","https://openalex.org/W2775653686","https://openalex.org/W2884023771","https://openalex.org/W2948768062","https://openalex.org/W2997546679","https://openalex.org/W3008214279","https://openalex.org/W3013979704","https://openalex.org/W3015362220","https://openalex.org/W3034775104","https://openalex.org/W3034873226","https://openalex.org/W3048190600","https://openalex.org/W3109641518","https://openalex.org/W3110041358","https://openalex.org/W3169524228","https://openalex.org/W3179257852","https://openalex.org/W3193693507","https://openalex.org/W3196105425","https://openalex.org/W3202720827","https://openalex.org/W3212934112","https://openalex.org/W4200121584","https://openalex.org/W4200421053","https://openalex.org/W4296622699","https://openalex.org/W4297399559","https://openalex.org/W4304481487","https://openalex.org/W4305072364","https://openalex.org/W4307113444","https://openalex.org/W4308462854","https://openalex.org/W4319074069","https://openalex.org/W4321021227","https://openalex.org/W4382567938","https://openalex.org/W4393190498","https://openalex.org/W6632551490","https://openalex.org/W6636950071","https://openalex.org/W6680483772","https://openalex.org/W6685042627","https://openalex.org/W6726030733","https://openalex.org/W6732103313"],"related_works":["https://openalex.org/W4389358162","https://openalex.org/W2111020819","https://openalex.org/W2377594161","https://openalex.org/W1837533151","https://openalex.org/W2296297476","https://openalex.org/W2329943782","https://openalex.org/W1578340400","https://openalex.org/W2365514879","https://openalex.org/W84513934","https://openalex.org/W15987807"],"abstract_inverted_index":{"Multilabel":[0],"feature":[1,105,181,238],"selection":[2,106,182,239],"solves":[3],"the":[4,13,27,36,57,68,76,82,122,131,151,172,180,218,225,230],"dimension":[5],"distress":[6],"of":[7,16,22,29,70,78,84,124,156,165],"high-dimensional":[8],"multilabel":[9,24,104],"data":[10,25,173],"by":[11,44],"selecting":[12],"optimal":[14],"subset":[15],"features.":[17],"Noisy":[18],"and":[19,98,145,153,175,196],"incomplete":[20],"labels":[21],"raw":[23],"hinder":[26],"acquisition":[28],"label-guided":[30],"information.":[31],"In":[32],"existing":[33],"approaches,":[34],"mapping":[35],"label":[37,49,60,64,72,86,201],"space":[38,43,61,129,174,195],"to":[39,47,120,190,199,216],"a":[40,88,110,125,186,192],"low-dimensional":[41],"latent":[42,59,85,95,111,127,133,142,146,158,176],"semantic":[45],"decomposition":[46],"mitigate":[48],"noise":[50],"is":[51,107,118,214],"considered":[52],"an":[53,208],"effective":[54,209],"strategy.":[55],"However,":[56],"decomposed":[58],"contains":[62],"redundant":[63,79],"information,":[65],"which":[66],"misleads":[67],"capture":[69],"potential":[71],"relevance.":[73],"To":[74],"eliminate":[75],"effect":[77],"information":[80,144,155],"on":[81,203,224],"extraction":[83],"correlations,":[87],"novel":[89],"method":[90,232],"named":[91],"SLOFS":[92,184,219],"via":[93,130],"shared":[94,115],"sublabel":[96,128,143,188,194,205],"structure":[97,114,152],"simultaneous":[99],"orthogonal":[100,112],"basis":[101],"clustering":[102,134,147],"for":[103],"proposed.":[108],"First,":[109],"base":[113],"(LOBSS)":[116],"term":[117,139],"engineered":[119],"guide":[121],"construction":[123],"redundancy-free":[126],"separated":[132],"center":[135,148],"structure.":[136,149],"The":[137,163,221],"LOBSS":[138],"simultaneously":[140],"retains":[141],"Moreover,":[150],"relevance":[154],"nonredundant":[157],"sublabels":[159],"are":[160],"fully":[161],"explored.":[162],"introduction":[164],"graph":[166,189],"regularization":[167,198],"ensures":[168],"structural":[169],"consistency":[170],"in":[171],"sublabels,":[177],"thus":[178],"helping":[179],"process.":[183],"employs":[185],"dynamic":[187,204],"obtain":[191],"high-quality":[193],"uses":[197],"constrain":[200],"correlations":[202],"projections.":[206],"Finally,":[207],"convergence":[210],"provable":[211],"optimization":[212],"scheme":[213],"proposed":[215],"solve":[217],"method.":[220],"experimental":[222],"studies":[223],"18":[226],"datasets":[227],"demonstrate":[228],"that":[229],"presented":[231],"performs":[233],"consistently":[234],"better":[235],"than":[236],"previous":[237],"methods.":[240]},"counts_by_year":[{"year":2026,"cited_by_count":11},{"year":2025,"cited_by_count":21},{"year":2024,"cited_by_count":11}],"updated_date":"2026-07-21T08:15:58.654021","created_date":"2025-10-10T00:00:00"}