{"id":"https://openalex.org/W4313008689","doi":"https://doi.org/10.1109/tkde.2022.3231660","title":"Label-Enhanced Graph Neural Network for Semi-Supervised Node Classification","display_name":"Label-Enhanced Graph Neural Network for Semi-Supervised Node Classification","publication_year":2022,"publication_date":"2022-12-23","ids":{"openalex":"https://openalex.org/W4313008689","doi":"https://doi.org/10.1109/tkde.2022.3231660"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2022.3231660","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3231660","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/A5056061158","display_name":"Le Yu","orcid":"https://orcid.org/0000-0002-4908-3199"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Le Yu","raw_affiliation_strings":["State Key Laboratory of Software Development Environment, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Software Development Environment, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081275566","display_name":"Leilei Sun","orcid":"https://orcid.org/0000-0002-0157-1716"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Leilei Sun","raw_affiliation_strings":["State Key Laboratory of Software Development Environment, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Software Development Environment, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053487836","display_name":"Bowen Du","orcid":"https://orcid.org/0000-0003-0975-2367"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bowen Du","raw_affiliation_strings":["State Key Laboratory of Software Development Environment, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Software Development Environment, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103014633","display_name":"Tongyu Zhu","orcid":"https://orcid.org/0000-0002-8948-3103"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tongyu Zhu","raw_affiliation_strings":["State Key Laboratory of Software Development Environment, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Software Development Environment, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109299440","display_name":"Weifeng Lv","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weifeng Lv","raw_affiliation_strings":["State Key Laboratory of Software Development Environment, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Software Development Environment, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5056061158"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":2.6191,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.91270757,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"35","issue":"11","first_page":"11529","last_page":"11540"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9987000226974487,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9987000226974487,"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/T11122","display_name":"Online Learning and Analytics","score":0.9700999855995178,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9520999789237976,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8560103178024292},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.617750883102417},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.6111639738082886},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.609207272529602},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5266194939613342},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5168445706367493},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4375927746295929},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4366164207458496},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.27457621693611145}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8560103178024292},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.617750883102417},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.6111639738082886},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.609207272529602},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5266194939613342},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5168445706367493},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4375927746295929},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4366164207458496},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.27457621693611145},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2022.3231660","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2022.3231660","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4768736148","display_name":null,"funder_award_id":"71901011","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7502749798","display_name":null,"funder_award_id":"62272023","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8480814412","display_name":null,"funder_award_id":"51991395","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":69,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1888005072","https://openalex.org/W2075010670","https://openalex.org/W2095705004","https://openalex.org/W2154851992","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2604314403","https://openalex.org/W2743104969","https://openalex.org/W2883725317","https://openalex.org/W2907492528","https://openalex.org/W2911286998","https://openalex.org/W2945827377","https://openalex.org/W2952205826","https://openalex.org/W2962756421","https://openalex.org/W2963919031","https://openalex.org/W2964051675","https://openalex.org/W2965857891","https://openalex.org/W2966398094","https://openalex.org/W2971933740","https://openalex.org/W2997461192","https://openalex.org/W2998269939","https://openalex.org/W3002924435","https://openalex.org/W3003795821","https://openalex.org/W3011667710","https://openalex.org/W3012871709","https://openalex.org/W3019011053","https://openalex.org/W3025936138","https://openalex.org/W3035649237","https://openalex.org/W3042770487","https://openalex.org/W3099375322","https://openalex.org/W3101553402","https://openalex.org/W3104097132","https://openalex.org/W3116768744","https://openalex.org/W3135958557","https://openalex.org/W3152893301","https://openalex.org/W3156681329","https://openalex.org/W3161072801","https://openalex.org/W3164473340","https://openalex.org/W3166627959","https://openalex.org/W3173673281","https://openalex.org/W3175971420","https://openalex.org/W3187966659","https://openalex.org/W3201150168","https://openalex.org/W3217672792","https://openalex.org/W4294170691","https://openalex.org/W6631190155","https://openalex.org/W6674330103","https://openalex.org/W6680434193","https://openalex.org/W6682494755","https://openalex.org/W6726497184","https://openalex.org/W6726873649","https://openalex.org/W6738964360","https://openalex.org/W6745537798","https://openalex.org/W6749077313","https://openalex.org/W6752110883","https://openalex.org/W6763701032","https://openalex.org/W6767710714","https://openalex.org/W6776072314","https://openalex.org/W6776488958","https://openalex.org/W6778401151","https://openalex.org/W6779961489","https://openalex.org/W6780017182","https://openalex.org/W6784568508","https://openalex.org/W6787550660","https://openalex.org/W6791820802","https://openalex.org/W6794579267","https://openalex.org/W6796549732","https://openalex.org/W6797673567"],"related_works":["https://openalex.org/W2468279273","https://openalex.org/W2354198838","https://openalex.org/W1989130879","https://openalex.org/W2103419012","https://openalex.org/W2988126442","https://openalex.org/W1974414866","https://openalex.org/W2063982682","https://openalex.org/W2338543196","https://openalex.org/W1544691147","https://openalex.org/W2039176012"],"abstract_inverted_index":{"Graph":[0],"Neural":[1],"Networks":[2],"(GNNs)":[3],"have":[4,53,97],"been":[5,54],"widely":[6],"applied":[7],"in":[8,19,111],"the":[9,24,32,37,42,46,59,62,67,70,79,88,98,106,138,151,157,164,168,183,190,204,214,221,241,247],"semi-supervised":[10],"node":[11,71,176,219],"classification":[12,43],"task,":[13],"where":[14],"a":[15,116,128,174],"key":[16],"point":[17],"lies":[18],"how":[20],"to":[21,56,96,156,181,201],"sufficiently":[22],"leverage":[23],"limited":[25],"but":[26,160,243],"valuable":[27],"label":[28,126,165,185],"information.":[29],"Most":[30],"of":[31,66,82,109,140,153,171,216,249],"classical":[33],"GNNs":[34],"solely":[35],"use":[36],"known":[38],"labels":[39,60,211],"for":[40,120,131],"computing":[41],"loss":[44],"at":[45,61],"output.":[47],"In":[48],"recent":[49],"years,":[50],"several":[51],"methods":[52,68,86],"designed":[55],"additionally":[57],"utilize":[58],"input.":[63],"One":[64],"part":[65],"augment":[69],"features":[72],"via":[73],"concatenating":[74],"or":[75],"adding":[76],"them":[77],"with":[78,207],"one-hot":[80],"encodings":[81],"labels,":[83,110],"while":[84],"other":[85],"optimize":[87],"graph":[89],"structure":[90],"by":[91],"assuming":[92],"neighboring":[93],"nodes":[94,133,142,154],"tend":[95],"same":[99,158],"label.":[100],"To":[101],"bring":[102],"into":[103,167],"full":[104],"play":[105],"rich":[107],"information":[108],"this":[112],"article":[113],"we":[114],"present":[115],"label-enhanced":[117],"learning":[118,169],"framework":[119],"GNNs,":[121],"which":[122],"first":[123],"models":[124],"each":[125,217],"as":[127],"virtual":[129],"center":[130],"intra-class":[132,250],"and":[134,143,188,212,230],"then":[135],"jointly":[136],"learns":[137],"representations":[139,152,248],"both":[141,228],"labels.":[144],"Our":[145],"approach":[146,235],"could":[147],"not":[148,237],"only":[149,238],"smooth":[150,246],"belonging":[155],"class,":[159],"also":[161,244],"explicitly":[162],"encode":[163],"semantics":[166],"process":[170],"GNNs.":[172],"Moreover,":[173],"training":[175,205,223],"selection":[177],"technique":[178],"is":[179,199],"provided":[180],"eliminate":[182],"potential":[184],"leakage":[186],"issue":[187],"guarantee":[189],"model":[191,222],"generalization":[192],"ability.":[193],"Finally,":[194],"an":[195],"adaptive":[196],"self-training":[197],"strategy":[198],"proposed":[200],"iteratively":[202],"enlarge":[203],"set":[206],"more":[208],"reliable":[209],"pseudo":[210],"distinguish":[213],"importance":[215],"pseudo-labeled":[218],"during":[220],"process.":[224],"Experimental":[225],"results":[226],"on":[227],"real-world":[229],"synthetic":[231],"datasets":[232],"demonstrate":[233],"our":[234],"can":[236],"consistently":[239],"outperform":[240],"state-of-the-arts,":[242],"effectively":[245],"nodes.":[251]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-17T09:09:15.849793","created_date":"2025-10-10T00:00:00"}
