{"id":"https://openalex.org/W4385764279","doi":"https://doi.org/10.24963/ijcai.2023/447","title":"Label Enhancement via Joint Implicit Representation Clustering","display_name":"Label Enhancement via Joint Implicit Representation Clustering","publication_year":2023,"publication_date":"2023-08-01","ids":{"openalex":"https://openalex.org/W4385764279","doi":"https://doi.org/10.24963/ijcai.2023/447"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2023/447","is_oa":true,"landing_page_url":"http://dx.doi.org/10.24963/ijcai.2023/447","pdf_url":"https://www.ijcai.org/proceedings/2023/0447.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2023/0447.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","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":["Nanjing University of Science and Technology","School of Computer Science and Engineering, Nanjing University of Science and Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology","institution_ids":["https://openalex.org/I36399199"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100371197","display_name":"Weiwei Li","orcid":"https://orcid.org/0000-0001-5781-5401"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weiwei Li","raw_affiliation_strings":["Nanjing University of Aeronautics and Astronautics","College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Aeronautics and Astronautics","institution_ids":["https://openalex.org/I9842412"]},{"raw_affiliation_string":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"last","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":["Nanjing University of Science and Technology","School of Computer Science and Engineering, Nanjing University of Science and Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology","institution_ids":["https://openalex.org/I36399199"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Nanjing University of Science and Technology, China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100371197"],"corresponding_institution_ids":["https://openalex.org/I9842412"],"apc_list":null,"apc_paid":null,"fwci":0.1872,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.42322469,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"4019","last_page":"4027"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9994000196456909,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9945999979972839,"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.992900013923645,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7635929584503174},{"id":"https://openalex.org/keywords/polysemy","display_name":"Polysemy","score":0.6491653919219971},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.6105775237083435},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6063293218612671},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5722382068634033},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5550054311752319},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5437695980072021},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4612722396850586},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4363546371459961},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.42846715450286865},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2858089804649353}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7635929584503174},{"id":"https://openalex.org/C2780276568","wikidata":"https://www.wikidata.org/wiki/Q191928","display_name":"Polysemy","level":2,"score":0.6491653919219971},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.6105775237083435},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6063293218612671},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5722382068634033},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5550054311752319},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5437695980072021},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4612722396850586},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4363546371459961},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.42846715450286865},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2858089804649353},{"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2023/447","is_oa":true,"landing_page_url":"http://dx.doi.org/10.24963/ijcai.2023/447","pdf_url":"https://www.ijcai.org/proceedings/2023/0447.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2023/447","is_oa":true,"landing_page_url":"http://dx.doi.org/10.24963/ijcai.2023/447","pdf_url":"https://www.ijcai.org/proceedings/2023/0447.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1216116233","display_name":null,"funder_award_id":"61906090","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2484870499","display_name":null,"funder_award_id":"62176123","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4655160836","display_name":null,"funder_award_id":"NJ2020022","funder_id":"https://openalex.org/F4320322438","funder_display_name":"Nanjing University of Aeronautics and Astronautics"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322438","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794"},{"id":"https://openalex.org/F4320324852","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4385764279.pdf"},"referenced_works_count":37,"referenced_works":["https://openalex.org/W43928053","https://openalex.org/W1522301498","https://openalex.org/W1583071929","https://openalex.org/W1950412479","https://openalex.org/W1959608418","https://openalex.org/W1978832675","https://openalex.org/W1991207049","https://openalex.org/W2163922914","https://openalex.org/W2194775991","https://openalex.org/W2330485005","https://openalex.org/W2540382275","https://openalex.org/W2604773025","https://openalex.org/W2730106296","https://openalex.org/W2788764852","https://openalex.org/W2807904173","https://openalex.org/W2808535973","https://openalex.org/W2905443329","https://openalex.org/W2963029648","https://openalex.org/W2963321416","https://openalex.org/W2964751466","https://openalex.org/W2966460909","https://openalex.org/W2983276939","https://openalex.org/W2990045899","https://openalex.org/W2997813432","https://openalex.org/W3035602763","https://openalex.org/W3037099311","https://openalex.org/W3096840866","https://openalex.org/W3115044877","https://openalex.org/W3130648157","https://openalex.org/W3142256053","https://openalex.org/W3156212584","https://openalex.org/W3157513212","https://openalex.org/W3174971432","https://openalex.org/W3206403665","https://openalex.org/W4206096925","https://openalex.org/W4236239536","https://openalex.org/W4382237485"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W4287117424","https://openalex.org/W4387506531","https://openalex.org/W2087346071","https://openalex.org/W2967848559","https://openalex.org/W4299831724","https://openalex.org/W4283803360"],"abstract_inverted_index":{"Label":[0],"distribution":[1,134],"is":[2],"an":[3,15],"effective":[4],"label":[5,9,30,59,67,82,126,133,149],"form":[6],"to":[7,35,50,96,114],"portray":[8],"polysemy":[10],"(i.e.,":[11],"the":[12,25,62,66,101,121,154],"cases":[13],"that":[14,152],"instance":[16,63,74,122,160],"can":[17,111],"be":[18,112],"described":[19],"by":[20,61],"multiple":[21],"labels":[22],"simultaneously).":[23],"However,":[24,69],"expensive":[26],"annotating":[27],"cost":[28],"of":[29,39,105],"distributions":[31,60],"limits":[32],"its":[33],"application":[34],"a":[36,90,131,146,163],"wider":[37],"range":[38],"practical":[40],"tasks.":[41],"Therefore,":[42,84],"LE":[43,55,118],"(label":[44],"enhancement)":[45],"techniques":[46],"are":[47],"extensively":[48],"studied":[49],"solve":[51],"this":[52,86],"problem.":[53],"Existing":[54],"algorithms":[56],"mostly":[57],"estimate":[58],"relation":[64,123],"or":[65,79,124],"relation.":[68],"they":[70],"suffer":[71],"from":[72],"biased":[73],"relations,":[75],"limited":[76],"model":[77,93,151],"capabilities,":[78],"suboptimal":[80],"local":[81,125],"correlations.":[83,127],"in":[85,162],"paper,":[87],"we":[88,129],"propose":[89],"deep":[91],"generative":[92,148],"called":[94],"JRC":[95,142],"simultaneously":[97],"learn":[98],"and":[99,108,137,159],"cluster":[100],"joint":[102,156],"implicit":[103,157],"representations":[104,158],"both":[106],"features":[107],"labels,":[109],"which":[110],"used":[113],"improve":[115],"any":[116],"existing":[117],"algorithm":[119],"involving":[120],"Besides,":[128],"develop":[130],"novel":[132,147],"recovery":[135],"module,":[136],"then":[138],"integrate":[139],"it":[140],"with":[141],"model,":[143],"thus":[144],"constituting":[145],"enhancement":[150],"utilizes":[153],"learned":[155],"clusters":[161],"principled":[164],"way.":[165],"Finally,":[166],"extensive":[167],"experiments":[168],"validate":[169],"our":[170],"proposal.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
