{"id":"https://openalex.org/W3111099392","doi":"https://doi.org/10.1609/aaai.v35i14.17529","title":"Label Confusion Learning to Enhance Text Classification Models","display_name":"Label Confusion Learning to Enhance Text Classification Models","publication_year":2021,"publication_date":"2021-05-18","ids":{"openalex":"https://openalex.org/W3111099392","doi":"https://doi.org/10.1609/aaai.v35i14.17529","mag":"3111099392"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v35i14.17529","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v35i14.17529","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v35i14.17529","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103941337","display_name":"Biyang Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I181679659","display_name":"Shanghai University of Finance and Economics","ror":"https://ror.org/00wtvfq62","country_code":"CN","type":"education","lineage":["https://openalex.org/I181679659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Biyang Guo","raw_affiliation_strings":["AI Lab, School of Information Management and Engineering, Shanghai University of Finance and Economics"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AI Lab, School of Information Management and Engineering, Shanghai University of Finance and Economics","institution_ids":["https://openalex.org/I181679659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003652858","display_name":"Songqiao Han","orcid":"https://orcid.org/0000-0002-2896-0607"},"institutions":[{"id":"https://openalex.org/I181679659","display_name":"Shanghai University of Finance and Economics","ror":"https://ror.org/00wtvfq62","country_code":"CN","type":"education","lineage":["https://openalex.org/I181679659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Songqiao Han","raw_affiliation_strings":["AI Lab, School of Information Management and Engineering, Shanghai University of Finance and Economics"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AI Lab, School of Information Management and Engineering, Shanghai University of Finance and Economics","institution_ids":["https://openalex.org/I181679659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101631160","display_name":"Han Xiao","orcid":"https://orcid.org/0000-0002-3548-3204"},"institutions":[{"id":"https://openalex.org/I181679659","display_name":"Shanghai University of Finance and Economics","ror":"https://ror.org/00wtvfq62","country_code":"CN","type":"education","lineage":["https://openalex.org/I181679659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Han","raw_affiliation_strings":["AI Lab, School of Information Management and Engineering, Shanghai University of Finance and Economics"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AI Lab, School of Information Management and Engineering, Shanghai University of Finance and Economics","institution_ids":["https://openalex.org/I181679659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013792358","display_name":"Hailiang Huang","orcid":"https://orcid.org/0000-0002-0009-6677"},"institutions":[{"id":"https://openalex.org/I181679659","display_name":"Shanghai University of Finance and Economics","ror":"https://ror.org/00wtvfq62","country_code":"CN","type":"education","lineage":["https://openalex.org/I181679659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hailiang Huang","raw_affiliation_strings":["AI Lab, School of Information Management and Engineering, Shanghai University of Finance and Economics"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AI Lab, School of Information Management and Engineering, Shanghai University of Finance and Economics","institution_ids":["https://openalex.org/I181679659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102026365","display_name":"Ting Lu","orcid":"https://orcid.org/0000-0001-5478-3678"},"institutions":[{"id":"https://openalex.org/I181679659","display_name":"Shanghai University of Finance and Economics","ror":"https://ror.org/00wtvfq62","country_code":"CN","type":"education","lineage":["https://openalex.org/I181679659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Lu","raw_affiliation_strings":["AI Lab, School of Information Management and Engineering, Shanghai University of Finance and Economics"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AI Lab, School of Information Management and Engineering, Shanghai University of Finance and Economics","institution_ids":["https://openalex.org/I181679659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I181679659"],"apc_list":null,"apc_paid":null,"fwci":6.3413,"has_fulltext":true,"cited_by_count":67,"citation_normalized_percentile":{"value":0.97476895,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"35","issue":"14","first_page":"12929","last_page":"12936"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9994000196456909,"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":0.9994000196456909,"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/T10028","display_name":"Topic Modeling","score":0.9987999796867371,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9975000023841858,"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/overfitting","display_name":"Overfitting","score":0.8057925701141357},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7192378640174866},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.687240481376648},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.6172274351119995},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5498509407043457},{"id":"https://openalex.org/keywords/multi-label-classification","display_name":"Multi-label classification","score":0.5005419254302979},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5001270771026611},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.47663959860801697},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.47336074709892273},{"id":"https://openalex.org/keywords/confusion","display_name":"Confusion","score":0.45601844787597656},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.45292747020721436},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.38906383514404297},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3865056335926056},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.31809261441230774},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1749570667743683}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8057925701141357},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7192378640174866},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.687240481376648},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6172274351119995},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5498509407043457},{"id":"https://openalex.org/C2776482837","wikidata":"https://www.wikidata.org/wiki/Q3553958","display_name":"Multi-label classification","level":2,"score":0.5005419254302979},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5001270771026611},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.47663959860801697},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.47336074709892273},{"id":"https://openalex.org/C2781140086","wikidata":"https://www.wikidata.org/wiki/Q557945","display_name":"Confusion","level":2,"score":0.45601844787597656},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.45292747020721436},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.38906383514404297},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3865056335926056},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31809261441230774},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1749570667743683},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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/C11171543","wikidata":"https://www.wikidata.org/wiki/Q41630","display_name":"Psychoanalysis","level":1,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v35i14.17529","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v35i14.17529","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs.aaai.org:article/17529","is_oa":true,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/17529","pdf_url":"https://ojs.aaai.org/index.php/AAAI/article/download/17529/17336","source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"Peer-reviewed Article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v35i14.17529","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v35i14.17529","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1832693441","https://openalex.org/W1965555277","https://openalex.org/W2064675550","https://openalex.org/W2112796928","https://openalex.org/W2120615054","https://openalex.org/W2131744502","https://openalex.org/W2153579005","https://openalex.org/W2170240176","https://openalex.org/W2183341477","https://openalex.org/W2187089797","https://openalex.org/W2250539671","https://openalex.org/W2330485005","https://openalex.org/W2407776548","https://openalex.org/W2577366047","https://openalex.org/W2736941579","https://openalex.org/W2750384547","https://openalex.org/W2756946152","https://openalex.org/W2765742186","https://openalex.org/W2778817245","https://openalex.org/W2787560479","https://openalex.org/W2799027221","https://openalex.org/W2808427340","https://openalex.org/W2896457183","https://openalex.org/W2948210185","https://openalex.org/W2949300694","https://openalex.org/W2949541494","https://openalex.org/W2949547296","https://openalex.org/W2950813464","https://openalex.org/W2950903920","https://openalex.org/W2962739339","https://openalex.org/W2962754271","https://openalex.org/W2963012544","https://openalex.org/W2963248507","https://openalex.org/W2963341956","https://openalex.org/W2963403868","https://openalex.org/W2963912736","https://openalex.org/W2964061809","https://openalex.org/W2964081807","https://openalex.org/W2965880440","https://openalex.org/W2970597249","https://openalex.org/W2975429091","https://openalex.org/W2996428491","https://openalex.org/W4294170691","https://openalex.org/W4385245566","https://openalex.org/W6641869264","https://openalex.org/W6656120923","https://openalex.org/W6666761814","https://openalex.org/W6691431627","https://openalex.org/W6747516836","https://openalex.org/W6766866963"],"related_works":["https://openalex.org/W1574414179","https://openalex.org/W4362597605","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4297676672","https://openalex.org/W4281702477","https://openalex.org/W4378510483","https://openalex.org/W4376166922","https://openalex.org/W2490526372","https://openalex.org/W4221142204"],"abstract_inverted_index":{"Representing":[0],"the":[1,8,17,24,27,54,102,141,157,164,177,206],"true":[2],"label":[3,88,131,153,160,207],"as":[4,31,118],"one-hot":[5,18,49,159],"vector":[6],"is":[7,195],"common":[9],"practice":[10],"in":[11,45,62,94],"training":[12,85,148],"text":[13,125,172],"classification":[14,126,166,173,187],"models.":[15,127,188],"However,":[16],"representation":[19],"may":[20,40,60],"not":[21,35],"adequately":[22],"reflect":[23],"relation":[25,104],"between":[26,143],"instance":[28,144],"and":[29,38,65,145,149,203],"labels,":[30],"labels":[32,44,138,146],"are":[33],"often":[34],"completely":[36],"independent":[37],"instances":[39],"relate":[41],"to":[42,52,56,100,122,133,155,205],"multiple":[43],"practice.":[46],"The":[47],"inadequate":[48],"representations":[50],"tend":[51],"train":[53],"model":[55,66],"be":[57],"over-confident,":[58],"which":[59],"result":[61],"arbitrary":[63],"prediction":[64],"overfitting,":[67],"especially":[68,196],"for":[69,181,198],"confused":[70,199],"datasets":[71,79,175,202],"(datasets":[72,80],"with":[73,81,87],"very":[74],"similar":[75],"labels)":[76],"or":[77,200],"noisy":[78,201],"labeling":[82],"errors).":[83],"While":[84],"models":[86],"smoothing":[89,208],"can":[90,129],"ease":[91],"this":[92,108],"problem":[93],"some":[95],"degree,":[96],"it":[97],"still":[98],"fails":[99],"capture":[101,134],"realistic":[103],"among":[105,137],"labels.":[106],"In":[107],"paper,":[109],"we":[110],"propose":[111],"a":[112,151],"novel":[113],"Label":[114],"Confusion":[115],"Model":[116],"(LCM)":[117],"an":[119],"enhancement":[120],"component":[121],"current":[123],"popular":[124],"LCM":[128,180,194],"learn":[130],"confusion":[132],"semantic":[135],"overlap":[136],"by":[139],"calculating":[140],"similarity":[142],"during":[147],"generate":[150],"better":[152],"distribution":[154],"replace":[156],"original":[158],"vector,":[161],"thus":[162],"improving":[163],"final":[165],"performance.":[167],"Extensive":[168],"experiments":[169,190],"on":[170],"five":[171],"benchmark":[174],"reveal":[176],"effectiveness":[178],"of":[179],"several":[182],"widely":[183],"used":[184],"deep":[185],"learning":[186],"Further":[189],"also":[191],"verify":[192],"that":[193],"helpful":[197],"superior":[204],"method.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":12},{"year":2021,"cited_by_count":5}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
