{"id":"https://openalex.org/W3165260809","doi":"https://doi.org/10.1109/tfuzz.2021.3082171","title":"Multilabel Feature Selection Based on Relative Discernibility Pair Matrix","display_name":"Multilabel Feature Selection Based on Relative Discernibility Pair Matrix","publication_year":2021,"publication_date":"2021-05-20","ids":{"openalex":"https://openalex.org/W3165260809","doi":"https://doi.org/10.1109/tfuzz.2021.3082171","mag":"3165260809"},"language":"en","primary_location":{"id":"doi:10.1109/tfuzz.2021.3082171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2021.3082171","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/A5103083745","display_name":"Erliang Yao","orcid":"https://orcid.org/0009-0006-3591-9406"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Erliang Yao","raw_affiliation_strings":["School of Computer and Information Technology and Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology and Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan, China","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100698996","display_name":"Deyu Li","orcid":"https://orcid.org/0000-0003-2489-9404"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Deyu Li","raw_affiliation_strings":["School of Computer and Information Technology and Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan, China"],"raw_orcid":"https://orcid.org/0000-0003-2489-9404","affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology and Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan, China","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101008166","display_name":"Yanhui Zhai","orcid":null},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanhui Zhai","raw_affiliation_strings":["School of Computer and Information Technology and Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology and Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan, China","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074521284","display_name":"Chao Zhang","orcid":"https://orcid.org/0000-0001-6248-9962"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Zhang","raw_affiliation_strings":["School of Computer and Information Technology and Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology and Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan, China","institution_ids":["https://openalex.org/I181877577"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I181877577"],"apc_list":null,"apc_paid":null,"fwci":3.8351,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":{"value":0.93963188,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"30","issue":"7","first_page":"2388","last_page":"2401"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":1.0,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9934999942779541,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9894999861717224,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6835962533950806},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6188054084777832},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6127023696899414},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5966619849205017},{"id":"https://openalex.org/keywords/rough-set","display_name":"Rough set","score":0.5726926326751709},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5605404376983643},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5521537065505981},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5338965654373169},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5020918846130371},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5004699230194092},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4762406647205353},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4143407940864563},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41154223680496216},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4041503071784973},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.33021003007888794}],"concepts":[{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6835962533950806},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6188054084777832},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6127023696899414},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5966619849205017},{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.5726926326751709},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5605404376983643},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5521537065505981},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5338965654373169},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5020918846130371},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5004699230194092},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4762406647205353},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4143407940864563},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41154223680496216},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4041503071784973},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.33021003007888794},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tfuzz.2021.3082171","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2021.3082171","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":[],"awards":[{"id":"https://openalex.org/G2205878603","display_name":"\u57fa\u4e8e\u6807\u8bb0\u6982\u5ff5\u76d1\u7763\u7684\u591a\u6807\u8bb0\u7c92\u8ba1\u7b97\u7406\u8bba\u4e0e\u7b97\u6cd5\u7814\u7a76","funder_award_id":"61672331","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2321207565","display_name":"\u57fa\u4e8e\u51b3\u7b56\u8574\u6db5\u7684\u77e5\u8bc6\u8868\u793a\u4e0e\u63a8\u7406\u7814\u7a76","funder_award_id":"61972238","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3155100723","display_name":"\u57fa\u4e8e\u5f62\u5f0f\u6982\u5ff5\u5206\u6790\u7684\u5173\u8054\u6570\u636e\u77e5\u8bc6\u8868\u793a\u4e0e\u63a8\u7406\u7814\u7a76","funder_award_id":"62072294","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7861765440","display_name":null,"funder_award_id":"61806116","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":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":56,"referenced_works":["https://openalex.org/W636917482","https://openalex.org/W1970696760","https://openalex.org/W1972490990","https://openalex.org/W1990519701","https://openalex.org/W1998815305","https://openalex.org/W1999954155","https://openalex.org/W2027654459","https://openalex.org/W2044170702","https://openalex.org/W2052684427","https://openalex.org/W2053463056","https://openalex.org/W2063249739","https://openalex.org/W2072371577","https://openalex.org/W2079680557","https://openalex.org/W2090630554","https://openalex.org/W2092845575","https://openalex.org/W2096393821","https://openalex.org/W2098093602","https://openalex.org/W2135533176","https://openalex.org/W2156935079","https://openalex.org/W2162845119","https://openalex.org/W2191800066","https://openalex.org/W2244035566","https://openalex.org/W2253239179","https://openalex.org/W2346610881","https://openalex.org/W2470167798","https://openalex.org/W2605997098","https://openalex.org/W2609332722","https://openalex.org/W2732347010","https://openalex.org/W2743621318","https://openalex.org/W2745134596","https://openalex.org/W2745346289","https://openalex.org/W2766239046","https://openalex.org/W2796330245","https://openalex.org/W2883654649","https://openalex.org/W2887527983","https://openalex.org/W2905467815","https://openalex.org/W2910328857","https://openalex.org/W2911043813","https://openalex.org/W2911424083","https://openalex.org/W2911964244","https://openalex.org/W2913673059","https://openalex.org/W2938834426","https://openalex.org/W2943963440","https://openalex.org/W2944017292","https://openalex.org/W2948768062","https://openalex.org/W2956917852","https://openalex.org/W2982507320","https://openalex.org/W2992732987","https://openalex.org/W2994713090","https://openalex.org/W2999798427","https://openalex.org/W3026982543","https://openalex.org/W3034776043","https://openalex.org/W3134776119","https://openalex.org/W4255833381","https://openalex.org/W6695711977","https://openalex.org/W6732103313"],"related_works":["https://openalex.org/W1974941418","https://openalex.org/W2101211876","https://openalex.org/W1605308969","https://openalex.org/W2392745962","https://openalex.org/W2380940517","https://openalex.org/W4293525103","https://openalex.org/W2358215018","https://openalex.org/W2345184372","https://openalex.org/W2374344280","https://openalex.org/W3200179079"],"abstract_inverted_index":{"In":[0,80],"multilabel":[1,22,25,46,70,87,143,167,183],"learning,":[2],"the":[3,64,92,108,118,122,151,192,204],"curse":[4],"of":[5,9,66,94,103,110,120,135,201],"dimensionality":[6],"is":[7,138,154,173],"one":[8],"major":[10],"challenges.":[11],"Existing":[12],"single-label":[13],"feature":[14,26,47,88,136,144,168],"selection":[15,89,145,169],"methods":[16,58,90,198],"cannot":[17,61],"be":[18],"directly":[19],"applied":[20,44],"to":[21,45,68],"data,":[23],"and":[24,160,165,187,203],"selections":[27,48],"have":[28],"thus":[29],"been":[30,43],"widely":[31],"studied.":[32],"As":[33],"an":[34],"effective":[35],"granular":[36],"computing":[37],"tool,":[38],"rough":[39,56,112],"set":[40],"theory":[41],"has":[42],"for":[49],"addressing":[50],"various":[51],"realistic":[52],"applications.":[53],"However,":[54],"existing":[55],"set-based":[57],"not":[59],"only":[60],"effectively":[62],"characterize":[63],"ability":[65],"features":[67,104],"distinguish":[69],"sample":[71,96,124],"pairs,":[72],"but":[73],"also":[74],"usually":[75],"own":[76],"high":[77],"time":[78],"complexity.":[79],"this":[81,129],"article,":[82],"we":[83],"propose":[84],"two":[85],"novel":[86,132],"from":[91],"perspective":[93],"discerning":[95],"pairs.":[97],"First,":[98],"relative":[99],"discernibility":[100],"pair":[101,125],"matrixes":[102],"are":[105,185],"defined":[106],"in":[107,199],"framework":[109],"fuzzy":[111],"set,":[113],"where":[114],"each":[115],"element":[116],"represents":[117],"degree":[119],"distinguishing":[121],"corresponding":[123],"by":[126,158],"features.":[127],"On":[128],"basis,":[130],"a":[131,141],"evaluation":[133],"measure":[134,153],"subsets":[137],"defined.":[139],"Afterwards,":[140],"heuristic":[142],"approach":[146,170],"titled":[147,171],"RDPM":[148],"based":[149],"on":[150,180],"proposed":[152,174,193],"put":[155],"forward.":[156],"Inspired":[157],"sampling":[159],"ensemble":[161],"strategies,":[162],"another":[163],"efficient":[164],"robust":[166],"RDPM_SE":[172],"as":[175],"well.":[176],"Finally,":[177],"extensive":[178],"experiments":[179],"13":[181],"real-world":[182],"datasets":[184],"conducted,":[186],"experimental":[188],"results":[189],"show":[190],"that":[191],"algorithms":[194],"outperform":[195],"seven":[196],"state-of-the-art":[197],"terms":[200],"performances":[202],"running":[205],"time.":[206]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":6}],"updated_date":"2026-08-08T01:25:22.217667","created_date":"2025-10-10T00:00:00"}