{"id":"https://openalex.org/W3174971432","doi":"https://doi.org/10.1109/tkde.2021.3093099","title":"Label Enhancement by Maintaining Positive and Negative Label Relation","display_name":"Label Enhancement by Maintaining Positive and Negative Label Relation","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3174971432","doi":"https://doi.org/10.1109/tkde.2021.3093099","mag":"3174971432"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2021.3093099","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3093099","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/A5072069474","display_name":"Xiuyi Jia","orcid":"https://orcid.org/0000-0002-9879-9855"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuyi Jia","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China, (e-mail: jiaxy@njust.edu.cn)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China, (e-mail: jiaxy@njust.edu.cn)","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001813491","display_name":"Yunan Lu","orcid":"https://orcid.org/0000-0001-8861-7897"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunan Lu","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China, (e-mail: luyn@njust.edu.cn)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China, (e-mail: luyn@njust.edu.cn)","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080881337","display_name":"Fangwen Zhang","orcid":"https://orcid.org/0000-0003-0500-0440"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fangwen Zhang","raw_affiliation_strings":["School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China, (e-mail: zhangfangwen@njust.edu.cn)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu, China, (e-mail: zhangfangwen@njust.edu.cn)","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":2.1837,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.89501156,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9929999709129333,"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/T11309","display_name":"Music and Audio Processing","score":0.9908999800682068,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7713205814361572},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.6969895362854004},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6889664530754089},{"id":"https://openalex.org/keywords/degree","display_name":"Degree (music)","score":0.5290115475654602},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5280985236167908},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.47449302673339844},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.45901811122894287},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4406091272830963},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42075905203819275},{"id":"https://openalex.org/keywords/multi-label-classification","display_name":"Multi-label classification","score":0.41894251108169556},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3796076774597168}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7713205814361572},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.6969895362854004},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6889664530754089},{"id":"https://openalex.org/C2775997480","wikidata":"https://www.wikidata.org/wiki/Q586277","display_name":"Degree (music)","level":2,"score":0.5290115475654602},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5280985236167908},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.47449302673339844},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45901811122894287},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4406091272830963},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42075905203819275},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.41894251108169556},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3796076774597168},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","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.2021.3093099","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3093099","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":[{"display_name":"Peace, Justice and strong institutions","score":0.6899999976158142,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1529085430","https://openalex.org/W1565746575","https://openalex.org/W1583071929","https://openalex.org/W1978832675","https://openalex.org/W2028851602","https://openalex.org/W2066454034","https://openalex.org/W2106115875","https://openalex.org/W2118712128","https://openalex.org/W2137306662","https://openalex.org/W2146241755","https://openalex.org/W2150926065","https://openalex.org/W2151989798","https://openalex.org/W2156935079","https://openalex.org/W2242753553","https://openalex.org/W2330485005","https://openalex.org/W2422823951","https://openalex.org/W2429267751","https://openalex.org/W2540382275","https://openalex.org/W2542840256","https://openalex.org/W2605572715","https://openalex.org/W2605997098","https://openalex.org/W2734609266","https://openalex.org/W2787932459","https://openalex.org/W2788329408","https://openalex.org/W2808535973","https://openalex.org/W2810042265","https://openalex.org/W2963346784","https://openalex.org/W2964989635","https://openalex.org/W2966460909","https://openalex.org/W2976049311","https://openalex.org/W3003278679","https://openalex.org/W3009009611","https://openalex.org/W6600827882","https://openalex.org/W6630792627","https://openalex.org/W6633774736","https://openalex.org/W6680735885","https://openalex.org/W6683584131","https://openalex.org/W6732436211","https://openalex.org/W6752930859"],"related_works":["https://openalex.org/W4234874385","https://openalex.org/W2399035783","https://openalex.org/W1585007175","https://openalex.org/W2382521049","https://openalex.org/W2323648130","https://openalex.org/W2144385241","https://openalex.org/W3161230432","https://openalex.org/W2157140558","https://openalex.org/W2378782423","https://openalex.org/W1967293071"],"abstract_inverted_index":{"Label":[0],"distribution":[1,59],"learning":[2,8],"(LDL)":[3],"is":[4,33,47],"a":[5,12,19,107,124],"novel":[6,108],"machine":[7],"paradigm":[9],"that":[10,111],"gives":[11],"description":[13],"degree":[14,129],"of":[15,54,71,130,146],"each":[16],"label":[17,41,44,58,103],"to":[18,37,49,117],"particular":[20],"instance.":[21],"But":[22],"many":[23,63],"existing":[24],"datasets":[25,52,142],"contain":[26],"only":[27],"simple":[28],"logical":[29,55],"labels,":[30],"since":[31],"it":[32],"difficult":[34],"and":[35,69,85,101,132],"time-consuming":[36],"directly":[38],"obtain":[39],"the":[40,75,80,128,133,144],"distribution.":[42],"So":[43],"enhancement":[45],"(LE)":[46],"proposed":[48,68],"convert":[50],"multi-label":[51],"consisting":[53],"labels":[56],"into":[57],"datasets.":[60],"In":[61],"recently,":[62],"LE":[64,95],"algorithms":[65],"have":[66],"been":[67],"most":[70],"them":[72],"concentrate":[73],"on":[74,98,139],"fitting":[76,131],"degree,":[77],"but":[78],"ignore":[79],"ordering":[81,134],"relation":[82],"between":[83,127],"positive":[84,100],"negative":[86,102],"labels.":[87],"Therefore,":[88],"in":[89],"this":[90],"paper,":[91],"we":[92],"propose":[93],"an":[94],"algorithm":[96,122],"based":[97],"maintaining":[99],"relation,":[104],"which":[105],"contains":[106],"ranking":[109,119],"loss":[110],"can":[112],"generate":[113],"different":[114,118],"penalties":[115],"according":[116],"errors.":[120],"Our":[121],"achieves":[123],"good":[125],"balance":[126],"relation.":[135],"The":[136],"experimental":[137],"results":[138],"several":[140],"real-world":[141],"validate":[143],"effectiveness":[145],"our":[147],"method.":[148]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
