{"id":"https://openalex.org/W2330485005","doi":"https://doi.org/10.1109/tkde.2016.2545658","title":"Label Distribution Learning","display_name":"Label Distribution Learning","publication_year":2016,"publication_date":"2016-03-23","ids":{"openalex":"https://openalex.org/W2330485005","doi":"https://doi.org/10.1109/tkde.2016.2545658","mag":"2330485005"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2016.2545658","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2016.2545658","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/A5074742406","display_name":"Xin Geng","orcid":"https://orcid.org/0000-0001-7729-0622"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xin Geng","raw_affiliation_strings":["School of Computer Science and Engineering, Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5074742406"],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":null,"apc_paid":null,"fwci":54.7745,"has_fulltext":false,"cited_by_count":663,"citation_normalized_percentile":{"value":0.99844105,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"28","issue":"7","first_page":"1734","last_page":"1748"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9998999834060669,"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":0.9998999834060669,"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/T11309","display_name":"Music and Audio Processing","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9884999990463257,"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/computer-science","display_name":"Computer science","score":0.8416184186935425},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6269081234931946},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5963502526283264},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5683165788650513},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.5441956520080566},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.4443172812461853},{"id":"https://openalex.org/keywords/multi-label-classification","display_name":"Multi-label classification","score":0.42054522037506104},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32736480236053467}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8416184186935425},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6269081234931946},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5963502526283264},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5683165788650513},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.5441956520080566},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.4443172812461853},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.42054522037506104},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32736480236053467},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2016.2545658","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2016.2545658","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":[],"awards":[{"id":"https://openalex.org/G8493858802","display_name":null,"funder_award_id":"61273300","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8804013185","display_name":null,"funder_award_id":"61232007","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W195533127","https://openalex.org/W205829674","https://openalex.org/W216283022","https://openalex.org/W1506281249","https://openalex.org/W1510526001","https://openalex.org/W1529085430","https://openalex.org/W1985258161","https://openalex.org/W1999954155","https://openalex.org/W2022505761","https://openalex.org/W2028851602","https://openalex.org/W2038624061","https://openalex.org/W2038790645","https://openalex.org/W2056983531","https://openalex.org/W2063683862","https://openalex.org/W2066454034","https://openalex.org/W2074683386","https://openalex.org/W2096175520","https://openalex.org/W2102667697","https://openalex.org/W2102705755","https://openalex.org/W2103568877","https://openalex.org/W2106115875","https://openalex.org/W2109317801","https://openalex.org/W2110119381","https://openalex.org/W2113023411","https://openalex.org/W2119466907","https://openalex.org/W2122030764","https://openalex.org/W2122347864","https://openalex.org/W2128532956","https://openalex.org/W2133510502","https://openalex.org/W2134305421","https://openalex.org/W2134974509","https://openalex.org/W2135533176","https://openalex.org/W2136621137","https://openalex.org/W2137306662","https://openalex.org/W2140335411","https://openalex.org/W2146241755","https://openalex.org/W2150373884","https://openalex.org/W2150926065","https://openalex.org/W2155144632","https://openalex.org/W2156935079","https://openalex.org/W2160842254","https://openalex.org/W2163808566","https://openalex.org/W2242753553","https://openalex.org/W2496585406","https://openalex.org/W2913340405","https://openalex.org/W4238530616","https://openalex.org/W4247809669","https://openalex.org/W4285719527","https://openalex.org/W6607976765","https://openalex.org/W6630424276","https://openalex.org/W6674650171","https://openalex.org/W6679959949"],"related_works":["https://openalex.org/W2353179089","https://openalex.org/W2923538289","https://openalex.org/W2353125546","https://openalex.org/W2470643824","https://openalex.org/W4400595174","https://openalex.org/W2349635380","https://openalex.org/W4353089801","https://openalex.org/W2353819554","https://openalex.org/W2359488321","https://openalex.org/W4281776617"],"abstract_inverted_index":{"Although":[0],"multi-label":[1,78],"learning":[2,35,40,71,79],"can":[3],"deal":[4],"with":[5,8],"many":[6],"problems":[7],"label":[9,38,48,62,129],"ambiguity,":[10],"it":[11],"does":[12],"not":[13],"fit":[14],"some":[15],"real":[16],"applications":[17],"well":[18],"where":[19],"the":[20,24,27,57,64,106,109,125,151,156,162,165],"overall":[21],"distribution":[22,39,49,130],"of":[23,26,45,54,108,128,150,158,164],"importance":[25,157],"labels":[28],"matters.":[29],"This":[30,84],"paper":[31,85],"proposes":[32,86],"a":[33,51,68,121],"novel":[34],"paradigm":[36],"named":[37],"(LDL)":[41],"for":[42,161],"such":[43],"kind":[44],"applications.":[46],"The":[47],"covers":[50],"certain":[52],"number":[53],"labels,":[55],"representing":[56],"degree":[58],"to":[59,104],"which":[60,73,154],"each":[61],"describes":[63],"instance.":[65],"LDL":[66,89,110,166],"is":[67],"more":[69],"general":[70],"framework":[72],"includes":[74],"both":[75],"single-label":[76],"and":[77,98,114,124,134,143],"as":[80],"its":[81],"special":[82,159],"cases.":[83],"six":[87,112],"working":[88],"algorithms":[90],"in":[91],"three":[92],"ways:":[93],"problem":[94],"transformation,":[95],"algorithm":[96,100],"adaptation,":[97],"specialized":[99,152],"design.":[101],"In":[102],"order":[103],"compare":[105],"performance":[107],"algorithms,":[111,153],"representative":[113],"diverse":[115],"evaluation":[116],"measures":[117],"are":[118,132],"selected":[119],"via":[120],"clustering":[122],"analysis,":[123],"first":[126],"batch":[127],"datasets":[131,146],"collected":[133],"made":[135],"publicly":[136],"available.":[137],"Experimental":[138],"results":[139],"on":[140],"one":[141],"artificial":[142],"15":[144],"real-world":[145],"show":[147],"clear":[148],"advantages":[149],"indicates":[155],"design":[160],"characteristics":[163],"problem.":[167]},"counts_by_year":[{"year":2026,"cited_by_count":15},{"year":2025,"cited_by_count":71},{"year":2024,"cited_by_count":85},{"year":2023,"cited_by_count":101},{"year":2022,"cited_by_count":99},{"year":2021,"cited_by_count":100},{"year":2020,"cited_by_count":68},{"year":2019,"cited_by_count":56},{"year":2018,"cited_by_count":39},{"year":2017,"cited_by_count":23},{"year":2016,"cited_by_count":6}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}
