{"id":"https://openalex.org/W4321608008","doi":"https://doi.org/10.1109/tfuzz.2023.3248060","title":"Learning Instance-Level Label Correlation Distribution for Multilabel Classification With Fuzzy Rough Sets","display_name":"Learning Instance-Level Label Correlation Distribution for Multilabel Classification With Fuzzy Rough Sets","publication_year":2023,"publication_date":"2023-02-23","ids":{"openalex":"https://openalex.org/W4321608008","doi":"https://doi.org/10.1109/tfuzz.2023.3248060"},"language":"en","primary_location":{"id":"doi:10.1109/tfuzz.2023.3248060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2023.3248060","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"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 Fuzzy Systems","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/A5011991792","display_name":"Xiaoya Che","orcid":"https://orcid.org/0000-0002-0833-2048"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoya Che","raw_affiliation_strings":["School of Mathematics and Physics, North China Electric Power University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0833-2048","affiliations":[{"raw_affiliation_string":"School of Mathematics and Physics, North China Electric Power University, Beijing, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069347046","display_name":"Degang Chen","orcid":"https://orcid.org/0000-0002-1135-9807"},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Degang Chen","raw_affiliation_strings":["School of Mathematics and Physics, North China Electric Power University, Beijing, China","Hebei Key Laboratory of Physics and Energy Technology, North China Electric Power University, Baoding, China"],"raw_orcid":"https://orcid.org/0000-0002-1135-9807","affiliations":[{"raw_affiliation_string":"School of Mathematics and Physics, North China Electric Power University, Beijing, China","institution_ids":["https://openalex.org/I153473198"]},{"raw_affiliation_string":"Hebei Key Laboratory of Physics and Energy Technology, North China Electric Power University, Baoding, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060583758","display_name":"Jusheng Mi","orcid":null},"institutions":[{"id":"https://openalex.org/I94611258","display_name":"Hebei Normal University","ror":"https://ror.org/004rbbw49","country_code":"CN","type":"education","lineage":["https://openalex.org/I94611258"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jusheng Mi","raw_affiliation_strings":["School of Mathematical Sciences, Hebei Normal University, Shijiazhuang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, Hebei Normal University, Shijiazhuang, China","institution_ids":["https://openalex.org/I94611258"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9814,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.88421449,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"31","issue":"8","first_page":"2871","last_page":"2884"},"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.9800000190734863,"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/correlation","display_name":"Correlation","score":0.6727414131164551},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6336841583251953},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5317429900169373},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5170938968658447},{"id":"https://openalex.org/keywords/multi-label-classification","display_name":"Multi-label classification","score":0.5061652064323425},{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.5040816068649292},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4801008999347687},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4683854877948761},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4659596085548401},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.45298582315444946},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.4516321122646332},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.43478259444236755},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.4184782803058624},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.38714420795440674}],"concepts":[{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.6727414131164551},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6336841583251953},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5317429900169373},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5170938968658447},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.5061652064323425},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.5040816068649292},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4801008999347687},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4683854877948761},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4659596085548401},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.45298582315444946},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.4516321122646332},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.43478259444236755},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.4184782803058624},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38714420795440674},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tfuzz.2023.3248060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2023.3248060","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"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 Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[{"id":"https://openalex.org/G1264795403","display_name":"\u7c97\u7cd9\u96c6\u6570\u636e\u5206\u6790\u7b97\u6cd5\u6cdb\u5316\u80fd\u529b\u7406\u8bba\u4e0e\u65b9\u6cd5\u7814\u7a76","funder_award_id":"12071131","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1435747777","display_name":null,"funder_award_id":"2022M711134","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G357500106","display_name":null,"funder_award_id":"62076088","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5106787634","display_name":null,"funder_award_id":"1220011129","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/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1484754041","https://openalex.org/W1978734360","https://openalex.org/W2021680742","https://openalex.org/W2027654459","https://openalex.org/W2052684427","https://openalex.org/W2053463056","https://openalex.org/W2061554433","https://openalex.org/W2070860530","https://openalex.org/W2074909580","https://openalex.org/W2077812306","https://openalex.org/W2094381401","https://openalex.org/W2100556411","https://openalex.org/W2111011053","https://openalex.org/W2114315281","https://openalex.org/W2129026672","https://openalex.org/W2135596587","https://openalex.org/W2148484209","https://openalex.org/W2155440340","https://openalex.org/W2176228818","https://openalex.org/W2519969774","https://openalex.org/W2588628126","https://openalex.org/W2605997098","https://openalex.org/W2743621318","https://openalex.org/W2745134596","https://openalex.org/W2936995161","https://openalex.org/W2938834426","https://openalex.org/W2952278429","https://openalex.org/W2972653537","https://openalex.org/W2976049311","https://openalex.org/W2983276939","https://openalex.org/W3043771091","https://openalex.org/W3080817222","https://openalex.org/W3096564284","https://openalex.org/W3112713339","https://openalex.org/W3144047752","https://openalex.org/W3196105425","https://openalex.org/W3208922547","https://openalex.org/W4239510810","https://openalex.org/W4255833381","https://openalex.org/W6686272741","https://openalex.org/W6761030284","https://openalex.org/W6780661845"],"related_works":["https://openalex.org/W2392963705","https://openalex.org/W2107349454","https://openalex.org/W2382278777","https://openalex.org/W1964260090","https://openalex.org/W2353240132","https://openalex.org/W2375932290","https://openalex.org/W2978519593","https://openalex.org/W2102746356","https://openalex.org/W2018750854","https://openalex.org/W4390066334"],"abstract_inverted_index":{"In":[0,134],"multilabel":[1,51,63,89,93,196,208],"learning,":[2],"research":[3],"on":[4,22,43,66,113,206,221],"label":[5,24,48,60,74,101,130,142,147,155,161],"correlation":[6,25,49,61,75,131,148],"provides":[7],"an":[8],"effective":[9],"solution":[10],"to":[11,27,85,100,117,136,166,190],"compress":[12],"the":[13,23,32,44,56,67,72,95,107,128,138,145,153,158,160,168,171,192,195,200,211,222],"hypothesis":[14],"space":[15,53,186],"of":[16,46,59,98,110,170,181,194,213,218],"classifiers.":[17],"However,":[18],"this":[19,81],"article":[20,82],"focus":[21],"adapted":[26],"overall":[28],"data,":[29],"while":[30],"ignoring":[31],"locally":[33],"targeted":[34],"information":[35,112],"presented":[36],"by":[37,105],"some":[38],"instances.":[39],"The":[40,178,203,216],"lack":[41],"exploration":[42],"distribution":[45,76,124,149],"local":[47,96,121],"in":[50,62,80,174,184],"instance":[52],"undoubtedly":[54],"limits":[55],"in-depth":[57],"application":[58],"learning.":[64],"Based":[65],"fuzzy":[68],"rough":[69],"set":[70],"theory,":[71],"instance-level":[73,129,146],"is":[77,102,132,150,164,187,224],"first":[78],"proposed":[79],"and":[83,198],"applied":[84],"design":[86],"a":[87,175],"novel":[88],"learner.":[90],"For":[91],"each":[92],"instance,":[94],"importance":[97],"features":[99],"quantitatively":[103,188],"analyzed,":[104],"considering":[106],"decisive":[108],"influence":[109],"input":[111,185],"decision":[114],"making.":[115],"According":[116],"coincidence":[118],"degree":[119],"between":[120,141],"feature":[122],"weight":[123],"for":[125],"different":[126],"labels,":[127],"constructed.":[133],"order":[135],"reflect":[137],"internal":[139],"relationship":[140],"variables":[143],"objectively,":[144],"integrated":[151],"into":[152],"empirical":[154],"relevance.":[156],"On":[157],"basis,":[159],"relevance":[162],"matrix":[163],"used":[165],"define":[167],"constraints":[169],"optimization":[172],"function":[173],"new":[176],"form.":[177],"relative":[179],"position":[180],"subseparating":[182],"hyperplanes":[183],"characterized":[189],"reduce":[191],"complexity":[193],"classifier":[197],"improve":[199],"learning":[201],"performance.":[202],"experiment":[204],"results":[205],"18":[207],"datasets":[209],"illustrate":[210],"effectiveness":[212],"our":[214],"algorithm.":[215],"impact":[217],"core":[219],"parameters":[220],"performance":[223],"also":[225],"dissected.":[226]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-19T07:52:34.831488","created_date":"2025-10-10T00:00:00"}
