{"id":"https://openalex.org/W2897810699","doi":"https://doi.org/10.1109/fuzz-ieee.2018.8491677","title":"Mutual Information Based K-Labelsets Ensemble for Multi-Label Classification","display_name":"Mutual Information Based K-Labelsets Ensemble for Multi-Label Classification","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2897810699","doi":"https://doi.org/10.1109/fuzz-ieee.2018.8491677","mag":"2897810699"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz-ieee.2018.8491677","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2018.8491677","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5114377922","display_name":"Ran Wang","orcid":"https://orcid.org/0000-0002-2586-5604"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran Wang","raw_affiliation_strings":["College of Mathematics and Statistics, Shenzhen University, Shenzhen, 518060, China","College of Mathematics and Statistics, Shenzhen University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Mathematics and Statistics, Shenzhen University, Shenzhen, 518060, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"College of Mathematics and Statistics, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008386708","display_name":"Sam Kwong","orcid":"https://orcid.org/0000-0001-7484-7261"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Sam Kwong","raw_affiliation_strings":["Department of Computer Science, City University of Hong Kong, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013880628","display_name":"Yuheng Jia","orcid":"https://orcid.org/0000-0002-3907-6550"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yuheng Jia","raw_affiliation_strings":["Department of Computer Science, City University of Hong Kong, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090589471","display_name":"Zhiqi Huang","orcid":"https://orcid.org/0000-0002-1506-1063"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqi Huang","raw_affiliation_strings":["Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen, 518060, China","Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen, 518060, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101504730","display_name":"Lang Wu","orcid":"https://orcid.org/0000-0003-3756-3731"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lang Wu","raw_affiliation_strings":["College of Management, Shenzhen University, Shenzhen, 518060, China","College of Management, Shenzhen University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Management, Shenzhen University, Shenzhen, 518060, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"College of Management, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9998000264167786,"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":0.9998000264167786,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9829000234603882,"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/T12254","display_name":"Machine Learning in Bioinformatics","score":0.9679999947547913,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.7643557190895081},{"id":"https://openalex.org/keywords/disjoint-sets","display_name":"Disjoint sets","score":0.7099056839942932},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.681668221950531},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.6363650560379028},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5596571564674377},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5309414863586426},{"id":"https://openalex.org/keywords/multi-label-classification","display_name":"Multi-label classification","score":0.44722241163253784},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43257641792297363},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.42138391733169556},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.41295963525772095},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40403982996940613},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26318657398223877}],"concepts":[{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.7643557190895081},{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.7099056839942932},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.681668221950531},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.6363650560379028},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5596571564674377},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5309414863586426},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.44722241163253784},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43257641792297363},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.42138391733169556},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.41295963525772095},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40403982996940613},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26318657398223877},{"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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fuzz-ieee.2018.8491677","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2018.8491677","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W125678093","https://openalex.org/W135042460","https://openalex.org/W1177539115","https://openalex.org/W1523738436","https://openalex.org/W2017305389","https://openalex.org/W2018901336","https://openalex.org/W2027266161","https://openalex.org/W2037248153","https://openalex.org/W2041328702","https://openalex.org/W2052684427","https://openalex.org/W2060754092","https://openalex.org/W2061351061","https://openalex.org/W2070960409","https://openalex.org/W2101825085","https://openalex.org/W2104739568","https://openalex.org/W2114315281","https://openalex.org/W2119466907","https://openalex.org/W2135533176","https://openalex.org/W2138290126","https://openalex.org/W2140335411","https://openalex.org/W2156935079","https://openalex.org/W2166912588","https://openalex.org/W2176228818","https://openalex.org/W2278864798","https://openalex.org/W2552092782","https://openalex.org/W2584559581","https://openalex.org/W2648561407","https://openalex.org/W2769747349","https://openalex.org/W6605125263","https://openalex.org/W6605540968","https://openalex.org/W6631340511","https://openalex.org/W6680102115","https://openalex.org/W6685347822"],"related_works":["https://openalex.org/W4256429076","https://openalex.org/W1971174658","https://openalex.org/W2099195351","https://openalex.org/W2466816617","https://openalex.org/W2348092930","https://openalex.org/W1970834875","https://openalex.org/W842936808","https://openalex.org/W3174028392","https://openalex.org/W2012063272","https://openalex.org/W2295624732"],"abstract_inverted_index":{"For":[0],"solving":[1],"multi-label":[2,61,188],"classification":[3,154],"problems,":[4,69],"traditional":[5],"random":[6],"K-labelsets":[7,76,119,164],"method":[8,78,148],"has":[9],"two":[10,52,68],"main":[11],"drawbacks:":[12],"1)":[13],"the":[14,31,38,56,60,87,97,128,131,134,145,159,177,194,197],"randomly":[15],"selected":[16,143],"label":[17,40,146],"set":[18,41],"may":[19,42],"result":[20],"in":[21,37,70],"highly":[22],"imbalanced":[23],"data":[24,189],"for":[25,141,179],"single-label":[26],"multi-class":[27,153,160],"learning,":[28],"and":[29,47,83,90,100,130,151,167],"2)":[30],"dependency":[32],"relations":[33],"among":[34],"different":[35,163],"labels":[36],"same":[39],"cause":[43],"serious":[44],"information":[45,82,89,123],"redundancy":[46,98],"overlap.":[48],"Both":[49],"of":[50,59,103,118,196],"these":[51,67],"drawbacks":[53],"can":[54],"affect":[55],"generalization":[57],"capability":[58],"learner.":[62],"In":[63],"order":[64],"to":[65,95,126,175],"overcome":[66],"this":[71],"paper,":[72],"we":[73],"propose":[74],"a":[75,116,152,168],"ensemble":[77,171],"based":[79,170],"on":[80,162,186],"mutual":[81,88,122],"joint":[84,91,136],"entropy.":[85],"First,":[86],"entropy":[92,137],"are":[93,124,165],"adopted":[94],"evaluate":[96],"level":[99,102],"imbalance":[101],"each":[104,114,142],"K-labelset.":[105],"Then,":[106],"disjoint":[107],"sampling":[108],"is":[109,138,149,156,173],"performed":[110],"iteratively,":[111],"where":[112],"during":[113],"iteration,":[115],"number":[117],"with":[120,133],"low":[121],"retained":[125],"be":[127],"candidates,":[129],"one":[132],"highest":[135],"selected.":[139],"Afterwards,":[140],"K-labelset,":[144],"powerset":[147],"employed":[150],"model":[155,172],"constructed.":[157],"Finally,":[158],"models":[161],"integrated,":[166],"voting":[169],"generated":[174],"perform":[176],"predictions":[178],"unseen":[180],"samples.":[181],"We":[182],"conduct":[183],"extensive":[184],"experiments":[185],"real-world":[187],"sets.":[190],"Experimental":[191],"results":[192],"demonstrate":[193],"effectiveness":[195],"proposed":[198],"method.":[199]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}