{"id":"https://openalex.org/W2951821459","doi":"https://doi.org/10.1145/3292500.3330840","title":"Adaptive Graph Guided Disambiguation for Partial Label Learning","display_name":"Adaptive Graph Guided Disambiguation for Partial Label Learning","publication_year":2019,"publication_date":"2019-07-25","ids":{"openalex":"https://openalex.org/W2951821459","doi":"https://doi.org/10.1145/3292500.3330840","mag":"2951821459"},"language":"en","primary_location":{"id":"doi:10.1145/3292500.3330840","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3292500.3330840","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-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/A5003193991","display_name":"Deng-Bao Wang","orcid":"https://orcid.org/0000-0002-6130-7220"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Deng-Bao Wang","raw_affiliation_strings":["Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100361415","display_name":"Li Li","orcid":"https://orcid.org/0009-0002-8638-457X"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Li","raw_affiliation_strings":["Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079083101","display_name":"Min-Ling Zhang","orcid":"https://orcid.org/0000-0003-1880-5918"},"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":"Min-Ling Zhang","raw_affiliation_strings":["Southeast University & Ministry of Education, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Southeast University & Ministry of Education, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5003193991"],"corresponding_institution_ids":["https://openalex.org/I142108993"],"apc_list":null,"apc_paid":null,"fwci":5.9195,"has_fulltext":false,"cited_by_count":79,"citation_normalized_percentile":{"value":0.96886319,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"83","last_page":"91"},"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":0.9872999787330627,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9815999865531921,"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":0.7074722051620483},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6709012389183044},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.6384300589561462},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5528659820556641},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5324654579162598},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5007152557373047},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.47238874435424805},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46168699860572815},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3221147656440735},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.12516537308692932}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7074722051620483},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6709012389183044},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.6384300589561462},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5528659820556641},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5324654579162598},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5007152557373047},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.47238874435424805},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46168699860572815},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3221147656440735},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.12516537308692932}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3292500.3330840","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3292500.3330840","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1974596106","https://openalex.org/W1981276685","https://openalex.org/W2010792435","https://openalex.org/W2024328138","https://openalex.org/W2027266161","https://openalex.org/W2029517229","https://openalex.org/W2035055162","https://openalex.org/W2106008047","https://openalex.org/W2108598243","https://openalex.org/W2114315281","https://openalex.org/W2137917285","https://openalex.org/W2153603270","https://openalex.org/W2221898772","https://openalex.org/W2274745179","https://openalex.org/W2338068721","https://openalex.org/W2393384312","https://openalex.org/W2531563875","https://openalex.org/W2561675875","https://openalex.org/W2591132901","https://openalex.org/W2592507807","https://openalex.org/W2620395638","https://openalex.org/W2808922551","https://openalex.org/W2997519153","https://openalex.org/W3000424784","https://openalex.org/W6738532226"],"related_works":["https://openalex.org/W4295532600","https://openalex.org/W3006513224","https://openalex.org/W2063823869","https://openalex.org/W2046456988","https://openalex.org/W2357409937","https://openalex.org/W2047973478","https://openalex.org/W2067569035","https://openalex.org/W2510582230","https://openalex.org/W2978674666","https://openalex.org/W4318818647"],"abstract_inverted_index":{"Partial":[0],"label":[1,69,108,150,190],"learning":[2,109,191],"aims":[3],"to":[4,35,52,62,129,175],"induce":[5],"a":[6,19,103,160],"multi-class":[7],"classifier":[8],"from":[9,93],"training":[10,87,155],"examples":[11],"where":[12],"each":[13],"of":[14,21,46,76,82,140],"them":[15],"is":[16,28,39],"associated":[17],"with":[18,118],"set":[20,70],"candidate":[22,48,68],"labels,":[23],"among":[24],"which":[25,163],"only":[26],"one":[27],"the":[29,43,73,80,90,131,136,141,166],"ground-truth":[30,54,167],"label.":[31],"The":[32],"common":[33],"strategy":[34,143],"train":[36],"predictive":[37,153],"model":[38,154,173],"disambiguation,":[40],"i.e.":[41],"differentiating":[42],"modeling":[44],"outputs":[45],"individual":[47],"labels":[49],"so":[50],"as":[51],"recover":[53],"labeling":[55,65,168],"information.":[56],"Recently,":[57],"feature-aware":[58],"disambiguation":[59,115,151],"was":[60],"proposed":[61,102],"generate":[63],"different":[64],"confidences":[66],"over":[67],"by":[71],"utilizing":[72],"graph":[74,113,122,171],"structure":[75,134],"feature":[77],"space.":[78],"However,":[79],"existence":[81],"noise":[83],"and":[84,127,152,172],"outliers":[85],"in":[86,144],"data":[88],"makes":[89],"similarity":[91,170],"derived":[92],"original":[94],"features":[95],"less":[96],"reliable.":[97],"To":[98],"this":[99],"end,":[100],"we":[101,158],"novel":[104],"approach":[105,148],"for":[106],"partial":[107,189],"based":[110],"on":[111],"adaptive":[112,121],"guided":[114],"(PL-AGGD).":[116],"Compared":[117],"fixed":[119],"graph,":[120],"could":[123],"be":[124],"more":[125],"robust":[126],"accurate":[128],"reveal":[130],"intrinsic":[132],"manifold":[133],"within":[135],"data.":[137],"Moreover,":[138],"instead":[139],"two-stage":[142],"previous":[145],"algorithms,":[146],"our":[147],"performs":[149,185],"simultaneously.":[156],"Specifically,":[157],"present":[159],"unified":[161],"framework":[162],"jointly":[164],"optimizes":[165],"confidences,":[169],"parameters":[174],"achieve":[176],"strong":[177],"generalization":[178],"performance.":[179],"Extensive":[180],"experiments":[181],"show":[182],"that":[183],"PL-AGGD":[184],"favorably":[186],"against":[187],"state-of-the-art":[188],"approaches.":[192]},"counts_by_year":[{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":17},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":2}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}