{"id":"https://openalex.org/W3128953992","doi":"https://doi.org/10.1109/tkde.2021.3054465","title":"A Novel Probabilistic Label Enhancement Algorithm for Multi-Label Distribution Learning","display_name":"A Novel Probabilistic Label Enhancement Algorithm for Multi-Label Distribution Learning","publication_year":2021,"publication_date":"2021-01-28","ids":{"openalex":"https://openalex.org/W3128953992","doi":"https://doi.org/10.1109/tkde.2021.3054465","mag":"3128953992"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2021.3054465","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3054465","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/A5101870059","display_name":"Chao Tan","orcid":"https://orcid.org/0000-0002-4064-2978"},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Tan","raw_affiliation_strings":["School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu, China"],"raw_orcid":"https://orcid.org/0000-0002-4064-2978","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I152031979"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100320969","display_name":"Sheng Chen","orcid":"https://orcid.org/0000-0001-6882-600X"},"institutions":[{"id":"https://openalex.org/I185163786","display_name":"King Abdulaziz University","ror":"https://ror.org/02ma4wv74","country_code":"SA","type":"education","lineage":["https://openalex.org/I185163786"]},{"id":"https://openalex.org/I43439940","display_name":"University of Southampton","ror":"https://ror.org/01ryk1543","country_code":"GB","type":"education","lineage":["https://openalex.org/I43439940"]}],"countries":["GB","SA"],"is_corresponding":false,"raw_author_name":"Sheng Chen","raw_affiliation_strings":["School of Electronics and Computer Science, University of Southampton, Southampton, U.K","King Abdulaziz University, Jeddah, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0001-6882-600X","affiliations":[{"raw_affiliation_string":"School of Electronics and Computer Science, University of Southampton, Southampton, U.K","institution_ids":["https://openalex.org/I43439940"]},{"raw_affiliation_string":"King Abdulaziz University, Jeddah, Saudi Arabia","institution_ids":["https://openalex.org/I185163786"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085214289","display_name":"Genlin Ji","orcid":"https://orcid.org/0000-0002-7475-1910"},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Genlin Ji","raw_affiliation_strings":["School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu, China"],"raw_orcid":"https://orcid.org/0000-0002-7475-1910","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I152031979"]}]},{"author_position":"last","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":false,"raw_author_name":"Xin Geng","raw_affiliation_strings":["School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu, China"],"raw_orcid":"https://orcid.org/0000-0001-7729-0622","affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0403,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.80599984,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"34","issue":"11","first_page":"5098","last_page":"5113"},"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":0.9789000153541565,"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/T10057","display_name":"Face and Expression Recognition","score":0.9728000164031982,"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":0.6923354864120483},{"id":"https://openalex.org/keywords/multi-label-classification","display_name":"Multi-label classification","score":0.6196387410163879},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5922737717628479},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5474080443382263},{"id":"https://openalex.org/keywords/intrinsic-dimension","display_name":"Intrinsic dimension","score":0.5054759979248047},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5038709044456482},{"id":"https://openalex.org/keywords/principle-of-maximum-entropy","display_name":"Principle of maximum entropy","score":0.45873820781707764},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4575480818748474},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4406552016735077},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4363935589790344},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.4344238042831421},{"id":"https://openalex.org/keywords/nonlinear-dimensionality-reduction","display_name":"Nonlinear dimensionality reduction","score":0.42222753167152405},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40612688660621643},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.06884455680847168}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6923354864120483},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.6196387410163879},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5922737717628479},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5474080443382263},{"id":"https://openalex.org/C30732413","wikidata":"https://www.wikidata.org/wiki/Q17092636","display_name":"Intrinsic dimension","level":3,"score":0.5054759979248047},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5038709044456482},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.45873820781707764},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4575480818748474},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4406552016735077},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4363935589790344},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.4344238042831421},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.42222753167152405},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40612688660621643},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.06884455680847168},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tkde.2021.3054465","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3054465","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"},{"id":"pmh:oai:eprints.soton.ac.uk:446513","is_oa":false,"landing_page_url":"https://eprints.soton.ac.uk/446513/2/TKDE2022_Nov.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306401019","display_name":"ePrints Soton (University of Southampton)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I43439940","host_organization_name":"University of Southampton","host_organization_lineage":["https://openalex.org/I43439940"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2814906339","display_name":null,"funder_award_id":"62076063","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6654493373","display_name":null,"funder_award_id":"61702270","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G878606470","display_name":null,"funder_award_id":"2017M621592","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"}],"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"},{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W195533127","https://openalex.org/W1565746575","https://openalex.org/W1970696760","https://openalex.org/W1971400763","https://openalex.org/W1995903905","https://openalex.org/W2000961858","https://openalex.org/W2006327656","https://openalex.org/W2014582301","https://openalex.org/W2022566595","https://openalex.org/W2052684427","https://openalex.org/W2057532020","https://openalex.org/W2066454034","https://openalex.org/W2074909580","https://openalex.org/W2077776048","https://openalex.org/W2094244309","https://openalex.org/W2114315281","https://openalex.org/W2116750654","https://openalex.org/W2119466907","https://openalex.org/W2137107481","https://openalex.org/W2141681031","https://openalex.org/W2147461642","https://openalex.org/W2156761667","https://openalex.org/W2160842254","https://openalex.org/W2242753553","https://openalex.org/W2330485005","https://openalex.org/W2387393241","https://openalex.org/W2390551652","https://openalex.org/W2540382275","https://openalex.org/W2553156677","https://openalex.org/W2568998735","https://openalex.org/W2789677693","https://openalex.org/W2796427615","https://openalex.org/W2808535973","https://openalex.org/W2894461463","https://openalex.org/W2910593176","https://openalex.org/W3003897323","https://openalex.org/W3005502035","https://openalex.org/W3042241776","https://openalex.org/W3105616927","https://openalex.org/W4301909677","https://openalex.org/W6607976765","https://openalex.org/W6683433006","https://openalex.org/W6694232893","https://openalex.org/W6734338310"],"related_works":["https://openalex.org/W2931531042","https://openalex.org/W2355395139","https://openalex.org/W1983074540","https://openalex.org/W2132734978","https://openalex.org/W2166963679","https://openalex.org/W3088634662","https://openalex.org/W2573981081","https://openalex.org/W2611114005","https://openalex.org/W2559803786","https://openalex.org/W2955487948"],"abstract_inverted_index":{"We":[0,21,135],"propose":[1,45],"a":[2,142],"novel":[3],"probabilistic":[4],"label":[5,13,29,53,62,95,112,122],"enhancement":[6],"algorithm,":[7],"called":[8],"PLEA,":[9],"to":[10,46,50,72,92,167],"solve":[11],"challenging":[12],"distribution":[14,30,54],"learning":[15,49,186],"(LDL)":[16],"for":[17,188],"multi-label":[18,170,185],"classification":[19,189],"problems.":[20],"adopt":[22],"the":[23,34,40,52,57,61,67,74,82,86,94,99,104,115,119,137,168,183],"well-known":[24],"maximum":[25,41,116],"entropy":[26,42,117],"model":[27],"based":[28,38],"learner.":[31,55],"However,":[32],"unlike":[33],"existing":[35],"LDL":[36,161,171],"algorithms":[37,187],"on":[39,141],"model,":[43,118],"we":[44],"use":[47],"manifold":[48,63,69],"enhance":[51],"Specifically,":[56],"supervised":[58],"information":[59],"in":[60,66,114,160],"is":[64,90],"utilized":[65],"feature":[68,77,83],"space":[70],"construction":[71],"improve":[73],"accuracy":[75,162],"of":[76],"extraction,":[78],"while":[79,129],"dramatically":[80],"reducing":[81],"dimension.":[84],"Then":[85],"robust":[87],"linear":[88],"regression":[89],"employed":[91],"estimate":[93],"distributions":[96,113,123],"associated":[97,110],"with":[98,182],"extracted":[100],"reduced-dimension":[101,106],"features.":[102],"Using":[103],"enhanced":[105],"features":[107],"and":[108,145,163],"their":[109],"estimated":[111,126],"unknown":[120],"true":[121],"can":[124],"be":[125],"more":[127],"accurately,":[128],"imposing":[130],"considerably":[131],"lower":[132],"computational":[133],"complexity.":[134],"evaluate":[136],"proposed":[138,155],"PLEA":[139,156,179],"method":[140,157],"wide-range":[143],"artificial":[144],"high-dimensional":[146],"real-world":[147],"datasets.":[148],"Experimental":[149],"results":[150,174],"obtained":[151],"demonstrate":[152],"that":[153,177],"our":[154,178],"has":[158],"advantages":[159],"runtime":[164],"performance,":[165],"compared":[166],"latest":[169],"approaches.":[172],"The":[173],"also":[175],"show":[176],"compares":[180],"favourably":[181],"state-of-the-arts":[184],"tasks.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}
