{"id":"https://openalex.org/W4386025966","doi":"https://doi.org/10.1109/tetci.2023.3302653","title":"Multi-Label Feature Selection via Positive or Negative Correlation","display_name":"Multi-Label Feature Selection via Positive or Negative Correlation","publication_year":2023,"publication_date":"2023-08-21","ids":{"openalex":"https://openalex.org/W4386025966","doi":"https://doi.org/10.1109/tetci.2023.3302653"},"language":"en","primary_location":{"id":"doi:10.1109/tetci.2023.3302653","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2023.3302653","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"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 Emerging Topics in Computational Intelligence","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/A5078988375","display_name":"Yaojin Lin","orcid":"https://orcid.org/0000-0002-6749-9534"},"institutions":[{"id":"https://openalex.org/I9356336","display_name":"Zhangzhou Normal University","ror":"https://ror.org/02vj1vm13","country_code":"CN","type":"education","lineage":["https://openalex.org/I9356336"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yaojin Lin","raw_affiliation_strings":["School of Computer Science, Minnan Normal University, Fujian, China"],"raw_orcid":"https://orcid.org/0000-0002-6749-9534","affiliations":[{"raw_affiliation_string":"School of Computer Science, Minnan Normal University, Fujian, China","institution_ids":["https://openalex.org/I9356336"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086101086","display_name":"Zhuoxin He","orcid":null},"institutions":[{"id":"https://openalex.org/I9356336","display_name":"Zhangzhou Normal University","ror":"https://ror.org/02vj1vm13","country_code":"CN","type":"education","lineage":["https://openalex.org/I9356336"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuoxin He","raw_affiliation_strings":["School of Computer Science, Minnan Normal University, Fujian, China"],"raw_orcid":"https://orcid.org/0009-0004-7934-2667","affiliations":[{"raw_affiliation_string":"School of Computer Science, Minnan Normal University, Fujian, China","institution_ids":["https://openalex.org/I9356336"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016126798","display_name":"Lei Guo","orcid":"https://orcid.org/0000-0001-7269-971X"},"institutions":[{"id":"https://openalex.org/I98834328","display_name":"Wuyi University","ror":"https://ror.org/059djzq42","country_code":"CN","type":"education","lineage":["https://openalex.org/I98834328"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Guo","raw_affiliation_strings":["Fujian Key Laboratory of Big Data Application and Intellectualization for Tea Industry, Wuyi University, Nanping, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory of Big Data Application and Intellectualization for Tea Industry, Wuyi University, Nanping, China","institution_ids":["https://openalex.org/I98834328"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069969191","display_name":"Weiping Ding","orcid":"https://orcid.org/0000-0002-3180-7347"},"institutions":[{"id":"https://openalex.org/I199305430","display_name":"Nantong University","ror":"https://ror.org/02afcvw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I199305430"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiping Ding","raw_affiliation_strings":["School of Information Science and Technology, Nantong University, Nantong, China"],"raw_orcid":"https://orcid.org/0000-0002-3180-7347","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Nantong University, Nantong, China","institution_ids":["https://openalex.org/I199305430"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5078988375"],"corresponding_institution_ids":["https://openalex.org/I9356336"],"apc_list":null,"apc_paid":null,"fwci":3.3466,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.93756543,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"8","issue":"1","first_page":"401","last_page":"415"},"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.988099992275238,"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/T10057","display_name":"Face and Expression Recognition","score":0.9635999798774719,"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/feature-selection","display_name":"Feature selection","score":0.7591713666915894},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6938040852546692},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6722047328948975},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6582392454147339},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6523908376693726},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6291982531547546},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.6115496158599854},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5378185510635376},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5371995568275452},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.4955641031265259},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.475551575422287},{"id":"https://openalex.org/keywords/multi-label-classification","display_name":"Multi-label classification","score":0.4654693603515625},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3707866072654724},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25069648027420044}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.7591713666915894},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6938040852546692},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6722047328948975},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6582392454147339},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6523908376693726},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6291982531547546},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.6115496158599854},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5378185510635376},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5371995568275452},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.4955641031265259},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.475551575422287},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.4654693603515625},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3707866072654724},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25069648027420044},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tetci.2023.3302653","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tetci.2023.3302653","pdf_url":null,"source":{"id":"https://openalex.org/S4210210251","display_name":"IEEE Transactions on Emerging Topics in Computational Intelligence","issn_l":"2471-285X","issn":["2471-285X"],"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 Emerging Topics in Computational Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7300000190734863,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G3711735600","display_name":null,"funder_award_id":"61976120","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5017658026","display_name":null,"funder_award_id":"2021J02049","funder_id":"https://openalex.org/F4320321878","funder_display_name":"Natural Science Foundation of Fujian Province"},{"id":"https://openalex.org/G620494539","display_name":null,"funder_award_id":"62076116","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/F4320321878","display_name":"Natural Science Foundation of Fujian Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W636917482","https://openalex.org/W1500895378","https://openalex.org/W1565746575","https://openalex.org/W1607198972","https://openalex.org/W1970696760","https://openalex.org/W1989368986","https://openalex.org/W2016944307","https://openalex.org/W2029517229","https://openalex.org/W2052684427","https://openalex.org/W2063249739","https://openalex.org/W2083488428","https://openalex.org/W2090630554","https://openalex.org/W2114315281","https://openalex.org/W2118712128","https://openalex.org/W2129026672","https://openalex.org/W2130187411","https://openalex.org/W2154053567","https://openalex.org/W2191800066","https://openalex.org/W2507677290","https://openalex.org/W2517538820","https://openalex.org/W2519969774","https://openalex.org/W2569112930","https://openalex.org/W2598849564","https://openalex.org/W2611743072","https://openalex.org/W2767943813","https://openalex.org/W2784178186","https://openalex.org/W2789758093","https://openalex.org/W2887527983","https://openalex.org/W2898240335","https://openalex.org/W2926842391","https://openalex.org/W2948768062","https://openalex.org/W2980962597","https://openalex.org/W2996966849","https://openalex.org/W3034775104","https://openalex.org/W3048190600","https://openalex.org/W3119688788","https://openalex.org/W3144047752","https://openalex.org/W3179257852","https://openalex.org/W3183680505","https://openalex.org/W3186062074","https://openalex.org/W3186290349","https://openalex.org/W3197047968","https://openalex.org/W3198831142","https://openalex.org/W3200378786","https://openalex.org/W3208124867","https://openalex.org/W4200421053","https://openalex.org/W4205711500","https://openalex.org/W4207053154","https://openalex.org/W4225289801","https://openalex.org/W4287626518","https://openalex.org/W4289236186","https://openalex.org/W4296622699","https://openalex.org/W4297399559","https://openalex.org/W6784935173"],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W2510961579","https://openalex.org/W156213964","https://openalex.org/W2050960118","https://openalex.org/W1972401983","https://openalex.org/W2782564536","https://openalex.org/W2527691073"],"abstract_inverted_index":{"Feature":[0],"selection,":[1],"a":[2,10,47,51,71,86,131,143,171],"meaningful":[3],"preprocessing":[4],"technique":[5],"in":[6,13,36,61,97,114,139],"machine":[7],"learning,":[8],"plays":[9],"key":[11],"role":[12],"multi-label":[14,22,100,133,217],"learning":[15,58],"to":[16,79,207],"select":[17],"more":[18],"discriminative":[19],"features.":[20],"Recently,":[21],"feature":[23,101,105,118,134,181],"selection":[24,102,135],"algorithms":[25],"based":[26],"on":[27,213],"sparse":[28,39,65],"regression":[29,40,66],"model":[30,67],"have":[31],"received":[32],"extensive":[33],"attention.":[34],"However,":[35],"the":[37,55,64,111,127,149,159,187,192,198],"existing":[38,99],"model,":[41],"feature-label":[42,73],"correlations":[43],"are":[44,184],"obtained":[45,185],"from":[46],"single":[48],"viewpoint":[49],"via":[50],"loss":[52],"function.":[53],"With":[54],"aim":[56],"of":[57,110],"richer":[59],"information,":[60],"this":[62,84,156],"article,":[63],"is":[68,94,106,119,137,146,153,168,175],"integrated":[69],"with":[70,108,121],"new":[72,87,132,172],"correlation,":[74,88,93],"which":[75],"allows":[76],"different":[77],"viewpoints":[78],"be":[80],"considered":[81],"simultaneously.":[82],"For":[83],"reason,":[85],"called":[89],"positive":[90,160],"or":[91,161],"negative":[92,162],"proposed.":[95],"Furthermore,":[96],"many":[98,115],"algorithms,":[103],"each":[104,117],"associated":[107,120],"all":[109],"labels,":[112],"while":[113],"scenarios,":[116],"only":[122],"some":[123],"labels.":[124],"Aiming":[125],"at":[126],"above":[128],"two":[129],"shortcomings,":[130],"algorithm":[136,200],"proposed":[138,199],"four":[140],"stages.":[141],"First,":[142],"pseudo-label":[144],"space":[145],"built":[147],"and":[148,166,180,203],"global":[150],"label":[151],"correlation":[152,163],"embedded":[154],"into":[155],"space.":[157],"Second,":[158],"between":[164],"features":[165,205],"labels":[167],"calculated.":[169],"Third,":[170],"objective":[173],"function":[174],"established.":[176],"The":[177],"weight":[178,193],"matrix":[179,194],"ranking":[182],"results":[183],"through":[186],"optimization":[188],"process.":[189],"Final,":[190],"using":[191],"as":[195],"prior":[196],"knowledge,":[197],"exploits":[201],"label-specific":[202],"label-group-specific":[204],"techniques":[206],"further":[208],"improve":[209],"performance.":[210,222],"Extensive":[211],"experiments":[212],"over":[214],"than":[215],"20":[216],"datasets":[218],"show":[219],"its":[220],"superior":[221]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":9}],"updated_date":"2026-05-10T08:33:47.465468","created_date":"2025-10-10T00:00:00"}
