{"id":"https://openalex.org/W4313427337","doi":"https://doi.org/10.1109/tkde.2022.3232114","title":"Robust Label and Feature Space Co-Learning for Multi-Label Classification","display_name":"Robust Label and Feature Space Co-Learning for Multi-Label Classification","publication_year":2023,"publication_date":"2023-01-02","ids":{"openalex":"https://openalex.org/W4313427337","doi":"https://doi.org/10.1109/tkde.2022.3232114"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2022.3232114","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3232114","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"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/A5101720700","display_name":"Zhifeng Liu","orcid":"https://orcid.org/0000-0002-4664-1140"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhifeng Liu","raw_affiliation_strings":["School of Computer Science and Communication Engineering, JiangSu University, Zhenjiang, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Communication Engineering, JiangSu University, Zhenjiang, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076710561","display_name":"Chuanjing Tang","orcid":"https://orcid.org/0000-0002-9805-233X"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuanjing Tang","raw_affiliation_strings":["School of Computer Science and Communication Engineering, JiangSu University, Zhenjiang, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Communication Engineering, JiangSu University, Zhenjiang, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068969296","display_name":"Stanley Ebhohimhen Abhadiomhen","orcid":"https://orcid.org/0000-0002-9509-1915"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]},{"id":"https://openalex.org/I11892038","display_name":"University of Nigeria","ror":"https://ror.org/01sn1yx84","country_code":"NG","type":"education","lineage":["https://openalex.org/I11892038"]}],"countries":["CN","NG"],"is_corresponding":false,"raw_author_name":"Stanley Ebhohimhen Abhadiomhen","raw_affiliation_strings":["School of Computer science and Communication Engineering, Jiangsu University, Zhenjiang, China","Department of Computer Science, University of Nigeria, Nsukka, Nigeria"],"affiliations":[{"raw_affiliation_string":"School of Computer science and Communication Engineering, Jiangsu University, Zhenjiang, China","institution_ids":["https://openalex.org/I115592961"]},{"raw_affiliation_string":"Department of Computer Science, University of Nigeria, Nsukka, Nigeria","institution_ids":["https://openalex.org/I11892038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015596649","display_name":"Xiang\u2010Jun Shen","orcid":"https://orcid.org/0000-0002-3359-8972"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiang-Jun Shen","raw_affiliation_strings":["School of Computer Science and Communication Engineering, JiangSu University, Zhenjiang, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Communication Engineering, JiangSu University, Zhenjiang, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100356508","display_name":"Yangyang Li","orcid":"https://orcid.org/0000-0002-5791-9443"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210120485","display_name":"Academy of Mathematics and Systems Science","ror":"https://ror.org/02jkmyk67","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210120485"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yangyang Li","raw_affiliation_strings":["Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210120485","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101720700"],"corresponding_institution_ids":["https://openalex.org/I115592961"],"apc_list":null,"apc_paid":null,"fwci":3.1314,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.93011652,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"35","issue":"11","first_page":"11846","last_page":"11859"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9973999857902527,"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":0.9973999857902527,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9243999719619751,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/multi-label-classification","display_name":"Multi-label classification","score":0.9105969071388245},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7498502135276794},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.648125410079956},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.588668167591095},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5541083216667175},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5292080044746399},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5172137022018433},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47619688510894775},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.472536563873291},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.44568079710006714},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44095444679260254},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4287649393081665},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4180183708667755},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34305518865585327},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.1535658836364746},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11920219659805298}],"concepts":[{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.9105969071388245},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7498502135276794},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.648125410079956},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.588668167591095},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5541083216667175},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5292080044746399},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5172137022018433},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47619688510894775},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.472536563873291},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.44568079710006714},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44095444679260254},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4287649393081665},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4180183708667755},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34305518865585327},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.1535658836364746},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11920219659805298},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2022.3232114","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3232114","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5099999904632568,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W79405465","https://openalex.org/W1515340688","https://openalex.org/W1546425806","https://openalex.org/W1565746575","https://openalex.org/W2027869746","https://openalex.org/W2052677124","https://openalex.org/W2087655037","https://openalex.org/W2114393161","https://openalex.org/W2156935079","https://openalex.org/W2343475530","https://openalex.org/W2519969774","https://openalex.org/W2527691073","https://openalex.org/W2576821058","https://openalex.org/W2594577230","https://openalex.org/W2611997167","https://openalex.org/W2626236803","https://openalex.org/W2783863635","https://openalex.org/W2794084401","https://openalex.org/W2891991685","https://openalex.org/W2895654662","https://openalex.org/W2921133856","https://openalex.org/W2948768062","https://openalex.org/W2981142240","https://openalex.org/W2985866789","https://openalex.org/W2996987977","https://openalex.org/W2997679978","https://openalex.org/W2998420437","https://openalex.org/W3011149291","https://openalex.org/W3015376289","https://openalex.org/W3020644100","https://openalex.org/W3034316692","https://openalex.org/W3036562957","https://openalex.org/W3039383207","https://openalex.org/W3081944915","https://openalex.org/W3109756233","https://openalex.org/W3116425023","https://openalex.org/W3126218682","https://openalex.org/W3128228480","https://openalex.org/W3130912157","https://openalex.org/W3131245832","https://openalex.org/W3135745701","https://openalex.org/W3144047752","https://openalex.org/W3148153051","https://openalex.org/W3149765555","https://openalex.org/W3153416049","https://openalex.org/W3155441061","https://openalex.org/W3156905473","https://openalex.org/W3162958367","https://openalex.org/W3170391983","https://openalex.org/W3171439488","https://openalex.org/W3183680505","https://openalex.org/W3183739743","https://openalex.org/W4232706428","https://openalex.org/W4287640433","https://openalex.org/W4300016061","https://openalex.org/W6603183647","https://openalex.org/W6632714361","https://openalex.org/W6677150689","https://openalex.org/W6712949048","https://openalex.org/W6772507390","https://openalex.org/W6775372008","https://openalex.org/W6784057281","https://openalex.org/W6787348287","https://openalex.org/W6790260322","https://openalex.org/W6792914034","https://openalex.org/W6929385289"],"related_works":["https://openalex.org/W2152992791","https://openalex.org/W2112835755","https://openalex.org/W2349674371","https://openalex.org/W4291951920","https://openalex.org/W2772359885","https://openalex.org/W3011471740","https://openalex.org/W2884580467","https://openalex.org/W2572315477","https://openalex.org/W2527691073","https://openalex.org/W2782564536"],"abstract_inverted_index":{"Multi-label":[0],"classification":[1,44,116],"remains":[2],"a":[3,25],"challenging":[4],"task":[5],"for":[6,37],"high-dimensional":[7],"data":[8,56],"samples":[9,57],"and":[10,28,58,85,92,105],"their":[11],"labels":[12],"both":[13],"increase":[14],"the":[15,109],"complexity":[16],"of":[17,120],"training":[18],"models.":[19],"In":[20],"this":[21,72],"paper,":[22],"we":[23],"propose":[24],"Robust":[26],"Label":[27],"Feature":[29],"Space":[30],"Co-Learning":[31],"method,":[32],"referred":[33],"to":[34],"as":[35],"RLFSCL,":[36],"multi-label":[38,43,115],"classification.":[39],"Different":[40],"from":[41,71],"traditional":[42,73],"methods":[45],"which":[46],"focus":[47],"on":[48,98,125],"feature":[49,84],"space":[50,70],"learning":[51],"through":[52],"regression":[53,74],"directly":[54],"between":[55],"labels,":[59],"our":[60,77],"proposed":[61,110],"method":[62],"can":[63,79],"further":[64],"learn":[65,80],"robust":[66],"low":[67,82],"rank":[68,83],"label":[69,86],"method.":[75],"Therefore,":[76],"RLFSCL":[78,111,121],"better":[81],"representations":[87],"simultaneously":[88],"in":[89],"original":[90],"noisy":[91],"high":[93],"dimensional":[94],"spaces.":[95],"Experimental":[96],"comparison":[97],"five":[99],"benchmark":[100],"datasets,":[101],"including":[102],"Rcv1s5,":[103],"Cal500,":[104],"Corel16k4":[106],"shows":[107],"that":[108],"algorithm":[112],"outperforms":[113],"state-of-the-art":[114],"methods.":[117],"The":[118],"code":[119],"is":[122],"made":[123],"available":[124],"<uri":[126],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[127],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/JingChuanTang/RLFSCL</uri>":[128],".":[129]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}