{"id":"https://openalex.org/W4414360250","doi":"https://doi.org/10.24963/ijcai.2025/743","title":"Partial Label Clustering","display_name":"Partial Label Clustering","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4414360250","doi":"https://doi.org/10.24963/ijcai.2025/743"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2025/743","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/743","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","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/A5101756484","display_name":"Yutong Xie","orcid":"https://orcid.org/0000-0003-3861-6778"},"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":"Yutong Xie","raw_affiliation_strings":["Chien-Shiung Wu College, Southeast University, Nanjing 210096, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chien-Shiung Wu College, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106708724","display_name":"Fuchao Yang","orcid":"https://orcid.org/0000-0002-5209-7153"},"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":"Fuchao Yang","raw_affiliation_strings":["College of Software Engineering, Southeast University, Nanjing 210096, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Software Engineering, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013880628","display_name":"Yuheng Jia","orcid":"https://orcid.org/0000-0002-3907-6550"},"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":"Yuheng Jia","raw_affiliation_strings":["Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications (Southeast University), Ministry of Education, China","School of Computer Science and Engineering, Southeast University, Nanjing 210096, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications (Southeast University), Ministry of Education, China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Computer Science and Engineering, Southeast University, Nanjing 210096, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6678","last_page":"6686"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.4417000114917755,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.4417000114917755,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.43540000915527344,"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/cluster-analysis","display_name":"Cluster analysis","score":0.7091000080108643},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5827000141143799},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5293999910354614},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5292999744415283},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.507099986076355},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48080000281333923},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.40380001068115234},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.3481000065803528},{"id":"https://openalex.org/keywords/constrained-clustering","display_name":"Constrained clustering","score":0.3476000130176544}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7091000080108643},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6603999733924866},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6302000284194946},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5827000141143799},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5293999910354614},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5292999744415283},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.507099986076355},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48080000281333923},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.40380001068115234},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3926999866962433},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38269999623298645},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.3481000065803528},{"id":"https://openalex.org/C27964816","wikidata":"https://www.wikidata.org/wiki/Q5164359","display_name":"Constrained clustering","level":5,"score":0.3476000130176544},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.32829999923706055},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.31520000100135803},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.30559998750686646},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.2964000105857849},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.2962000072002411},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.28940001130104065},{"id":"https://openalex.org/C146599234","wikidata":"https://www.wikidata.org/wiki/Q511093","display_name":"Centroid","level":2,"score":0.28859999775886536},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28130000829696655},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.27480000257492065},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2745000123977661},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.26899999380111694},{"id":"https://openalex.org/C2778459887","wikidata":"https://www.wikidata.org/wiki/Q6787865","display_name":"Matrix completion","level":3,"score":0.2623000144958496},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.25519999861717224},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.2540999948978424}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2025/743","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/743","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Partial":[0],"label":[1,25,39,82,127,149],"learning":[2,9,119],"(PLL)":[3],"is":[4,26],"a":[5,17,60,91,134,146],"significant":[6],"weakly":[7],"supervised":[8],"framework,":[10],"where":[11],"each":[12],"training":[13],"example":[14],"corresponds":[15],"to":[16,51,78,137],"set":[18,92],"of":[19,45,63,93],"candidate":[20,76],"labels":[21,50,77],"and":[22,73,95,109,129,171,174,186],"only":[23,179],"one":[24],"the":[27,31,37,46,53,70,75,80,85,100,106],"ground-truth":[28,81],"label.":[29],"For":[30],"first":[32,58],"time,":[33],"this":[34],"paper":[35],"investigates":[36],"partial":[38,49],"clustering":[40,54,154,169],"problem,":[41],"which":[42],"takes":[43],"advantage":[44],"limited":[47,180],"available":[48,190],"improve":[52,153],"performance.":[55,155],"Specifically,":[56],"we":[57,89,104,122],"construct":[59,90],"weight":[61,86,124],"matrix":[62,125,150],"examples":[64],"based":[65,83,98,112],"on":[66,84,99,113],"their":[67],"relationships":[68],"in":[69],"feature":[71],"space":[72],"disambiguate":[74],"estimate":[79],"matrix.":[87],"Then,":[88],"must-link":[94,108],"cannot-link":[96,110],"constraints":[97,111,131],"disambiguation":[101],"results.":[102],"Moreover,":[103],"propagate":[105],"initial":[107],"an":[114],"adversarial":[115],"prior":[116],"promoted":[117],"dual-graph":[118],"approach.":[120],"Finally,":[121],"integrate":[123],"construction,":[126],"disambiguation,":[128],"pairwise":[130],"propagation":[132],"into":[133],"joint":[135],"model":[136],"achieve":[138],"mutual":[139],"enhancement.":[140],"We":[141],"also":[142],"theoretically":[143],"prove":[144],"that":[145],"better":[147],"disambiguated":[148],"can":[151],"help":[152],"Comprehensive":[156],"experiments":[157],"demonstrate":[158],"our":[159],"method":[160],"realizes":[161],"superior":[162],"performance":[163],"when":[164,178],"comparing":[165],"with":[166],"state-of-the-art":[167],"constrained":[168],"methods,":[170],"outperforms":[172],"PLL":[173,176],"semi-supervised":[175],"methods":[177],"samples":[181],"are":[182,188],"annotated.":[183],"The":[184],"code":[185],"appendix":[187],"publicly":[189],"at":[191],"https://github.com/xyt-ml/PLC.":[192]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
