{"id":"https://openalex.org/W4378195015","doi":"https://doi.org/10.1109/tnnls.2023.3273255","title":"HeGCL: Advance Self-Supervised Learning in Heterogeneous Graph-Level Representation","display_name":"HeGCL: Advance Self-Supervised Learning in Heterogeneous Graph-Level Representation","publication_year":2023,"publication_date":"2023-05-25","ids":{"openalex":"https://openalex.org/W4378195015","doi":"https://doi.org/10.1109/tnnls.2023.3273255","pmid":"https://pubmed.ncbi.nlm.nih.gov/37227906"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3273255","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3273255","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5090123380","display_name":"Gen Shi","orcid":"https://orcid.org/0000-0002-1717-4053"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Gen Shi","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-1717-4053","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034415838","display_name":"Yifan Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifan Zhu","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7695-1633","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001710920","display_name":"Jian K. Liu","orcid":"https://orcid.org/0000-0002-5391-7213"},"institutions":[{"id":"https://openalex.org/I130828816","display_name":"University of Leeds","ror":"https://ror.org/024mrxd33","country_code":"GB","type":"education","lineage":["https://openalex.org/I130828816"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jian K. Liu","raw_affiliation_strings":["School of Computing, University of Leeds, Leeds, U.K"],"raw_orcid":"https://orcid.org/0000-0002-5391-7213","affiliations":[{"raw_affiliation_string":"School of Computing, University of Leeds, Leeds, U.K","institution_ids":["https://openalex.org/I130828816"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100449095","display_name":"Xuesong Li","orcid":"https://orcid.org/0000-0003-1570-277X"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuesong Li","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-1570-277X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5090123380"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":3.4082,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.93780832,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"35","issue":"10","first_page":"13914","last_page":"13925"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9993000030517578,"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":0.9993000030517578,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9825000166893005,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9807999730110168,"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":0.7447112798690796},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.596973180770874},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5804263353347778},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.539837121963501},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.47302886843681335},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4636093080043793},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.42843541502952576},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3443666100502014}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7447112798690796},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.596973180770874},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5804263353347778},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.539837121963501},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.47302886843681335},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4636093080043793},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.42843541502952576},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3443666100502014},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"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/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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tnnls.2023.3273255","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3273255","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:37227906","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37227906","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/6fc9b9ea-e68b-4ba4-af74-b6dae40940a9","is_oa":false,"landing_page_url":"https://research.birmingham.ac.uk/en/publications/6fc9b9ea-e68b-4ba4-af74-b6dae40940a9","pdf_url":null,"source":{"id":"https://openalex.org/S4306402634","display_name":"University of Birmingham Research Portal (University of Birmingham)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79619799","host_organization_name":"University of Birmingham","host_organization_lineage":["https://openalex.org/I79619799"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Shi , G , Zhu , Y , Liu , J K & Li , X 2023 , ' HeGCL : Advance Self-Supervised Learning in Heterogeneous Graph-Level Representation ' , IEEE Transactions on Neural Networks and Learning Systems . https://doi.org/10.1109/tnnls.2023.3273255","raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1455365679","display_name":null,"funder_award_id":"62071049","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5687068967","display_name":null,"funder_award_id":"61801026","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8244367932","display_name":null,"funder_award_id":"2022M711814","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1998752664","https://openalex.org/W2099438806","https://openalex.org/W2154851992","https://openalex.org/W2156770396","https://openalex.org/W2173027866","https://openalex.org/W2461470610","https://openalex.org/W2594183968","https://openalex.org/W2604314403","https://openalex.org/W2743104969","https://openalex.org/W2792485195","https://openalex.org/W2887997457","https://openalex.org/W2911286998","https://openalex.org/W2962756421","https://openalex.org/W2963091558","https://openalex.org/W2963919031","https://openalex.org/W2965857891","https://openalex.org/W2997461192","https://openalex.org/W3012816161","https://openalex.org/W3021975806","https://openalex.org/W3036446966","https://openalex.org/W3108202858","https://openalex.org/W3129758539","https://openalex.org/W3152893301","https://openalex.org/W3172710079","https://openalex.org/W3175971420","https://openalex.org/W3179367583","https://openalex.org/W3181240463","https://openalex.org/W3193043614","https://openalex.org/W4212927759","https://openalex.org/W4243316134","https://openalex.org/W4282827695","https://openalex.org/W4294170691","https://openalex.org/W4307340141","https://openalex.org/W4309096516","https://openalex.org/W4315630824","https://openalex.org/W6677886600","https://openalex.org/W6717434760","https://openalex.org/W6726873649","https://openalex.org/W6730084236","https://openalex.org/W6738964360","https://openalex.org/W6745537798","https://openalex.org/W6755573351","https://openalex.org/W6758623387","https://openalex.org/W6760001035","https://openalex.org/W6766156693","https://openalex.org/W6770592035","https://openalex.org/W6838913300","https://openalex.org/W6879715561"],"related_works":["https://openalex.org/W2062195135","https://openalex.org/W2795079307","https://openalex.org/W2793058541","https://openalex.org/W1983629434","https://openalex.org/W2055929693","https://openalex.org/W4324271173","https://openalex.org/W1588041347","https://openalex.org/W4285218279","https://openalex.org/W4386136067","https://openalex.org/W4286858940"],"abstract_inverted_index":{"Representation":[0],"learning":[1,32,125],"in":[2,89],"heterogeneous":[3,104,116,134],"graphs":[4,16,105],"with":[5,144],"massive":[6],"unlabeled":[7],"data":[8],"has":[9],"aroused":[10],"great":[11],"interest.":[12],"The":[13,127],"heterogeneity":[14],"of":[15,49,79,103,203,219],"not":[17,86],"only":[18],"contains":[19],"rich":[20],"information,":[21,151],"but":[22],"also":[23,214],"raises":[24],"difficult":[25],"barriers":[26],"to":[27,55,226],"designing":[28],"unsupervised":[29,67],"or":[30,66],"self-supervised":[31,65,115],"(SSL)":[33],"strategies.":[34],"Existing":[35],"methods":[36],"such":[37],"as":[38],"random":[39],"walk-based":[40],"approaches":[41],"are":[42,69,76],"mainly":[43],"dependent":[44],"on":[45,122,194],"the":[46,53,100,136,140,145,152,156,170,187,201,204,217],"proximity":[47],"information":[48,178],"neighbors":[50],"and":[51,84,139,160,182,189,197,210],"lack":[52],"ability":[54],"integrate":[56],"node":[57,173],"features":[58],"into":[59],"a":[60,93,114,166,223],"higher-level":[61],"representation.":[62],"Furthermore,":[63],"previous":[64],"frameworks":[68],"usually":[70],"designed":[71],"for":[72,132],"node-level":[73,196],"tasks,":[74],"which":[75],"commonly":[77],"short":[78],"capturing":[80],"global":[81,101,181],"graph":[82,117],"properties":[83,102,163],"may":[85],"perform":[87],"well":[88],"graph-level":[90,162,198,227],"tasks.":[91,228],"Therefore,":[92],"label-free":[94],"framework":[95],"that":[96,148,216],"can":[97],"better":[98],"capture":[99],"is":[106],"urgently":[107],"required.":[108],"In":[109],"this":[110],"article,":[111],"we":[112],"propose":[113],"neural":[118],"network":[119],"(GNN)":[120],"based":[121],"cross-view":[123],"contrastive":[124],"(HeGCL).":[126],"HeGCL":[128,171],"presents":[129],"two":[130],"views":[131],"encoding":[133],"graphs:":[135],"meta-path":[137,146,190],"view":[138,147,154],"outline":[141,153,188],"view.":[142],"Compared":[143],"provides":[149],"semantic":[150,183],"encodes":[155],"complex":[157],"edge":[158],"relations":[159],"captures":[161],"by":[164],"using":[165],"nonlocal":[167,220],"block.":[168],"Thus,":[169],"learns":[172],"embeddings":[174],"through":[175],"maximizing":[176],"mutual":[177],"(MI)":[179],"between":[180],"representations":[184],"coming":[185],"from":[186],"view,":[191],"respectively.":[192],"Experiments":[193],"both":[195],"tasks":[199],"show":[200,215],"superiority":[202],"proposed":[205],"model":[206],"over":[207],"other":[208],"methods,":[209],"further":[211],"exploration":[212],"studies":[213],"introduction":[218],"block":[221],"brings":[222],"significant":[224],"contribution":[225]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
