{"id":"https://openalex.org/W4405193820","doi":"https://doi.org/10.3390/sym16121631","title":"HybridGNN: A Self-Supervised Graph Neural Network for Efficient Maximum Matching in Bipartite Graphs","display_name":"HybridGNN: A Self-Supervised Graph Neural Network for Efficient Maximum Matching in Bipartite Graphs","publication_year":2024,"publication_date":"2024-12-09","ids":{"openalex":"https://openalex.org/W4405193820","doi":"https://doi.org/10.3390/sym16121631"},"language":"en","primary_location":{"id":"doi:10.3390/sym16121631","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym16121631","pdf_url":"https://www.mdpi.com/2073-8994/16/12/1631/pdf?version=1733739096","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/16/12/1631/pdf?version=1733739096","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5107827043","display_name":"C. Y. Pan","orcid":null},"institutions":[{"id":"https://openalex.org/I3132008252","display_name":"Nanjing Foreign Language School","ror":"https://ror.org/03wvwbe92","country_code":"CN","type":"education","lineage":["https://openalex.org/I3132008252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chun-Hui Pan","raw_affiliation_strings":["Shanghai World Foreign Language Academy, Shanghai 200233, China"],"raw_orcid":"https://orcid.org/0009-0001-5937-1282","affiliations":[{"raw_affiliation_string":"Shanghai World Foreign Language Academy, Shanghai 200233, China","institution_ids":["https://openalex.org/I3132008252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112119338","display_name":"Yi Qu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210146919","display_name":"Shanghai Industrial Technology Institute","ror":"https://ror.org/03j1pdd39","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210146919"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Qu","raw_affiliation_strings":["Shanghai Aerospace Electronic Technology Institute, Shanghai 201109, China"],"raw_orcid":"https://orcid.org/0009-0001-4977-5099","affiliations":[{"raw_affiliation_string":"Shanghai Aerospace Electronic Technology Institute, Shanghai 201109, China","institution_ids":["https://openalex.org/I4210146919"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yao Yao","orcid":"https://orcid.org/0009-0008-2530-981X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao Yao","raw_affiliation_strings":["Shenzhen Nanshan Experimental Education Group OCT Senior High School, Shenzhen 518058, China"],"raw_orcid":"https://orcid.org/0009-0008-2530-981X","affiliations":[{"raw_affiliation_string":"Shenzhen Nanshan Experimental Education Group OCT Senior High School, Shenzhen 518058, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010647258","display_name":"Mujiangshan Wang","orcid":"https://orcid.org/0000-0003-0950-4558"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mu-Jiang-Shan Wang","raw_affiliation_strings":["Institute of Advanced Computing and Digital Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China"],"raw_orcid":"https://orcid.org/0000-0003-0950-4558","affiliations":[{"raw_affiliation_string":"Institute of Advanced Computing and Digital Engineering, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China","institution_ids":["https://openalex.org/I4210145761","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5010647258"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210145761"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":1.3892,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.84801918,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"16","issue":"12","first_page":"1631","last_page":"1631"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","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/T11273","display_name":"Advanced Graph Neural Networks","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/T12292","display_name":"Graph Theory and Algorithms","score":0.9934999942779541,"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/T11948","display_name":"Machine Learning in Materials Science","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.8421613574028015},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6432463526725769},{"id":"https://openalex.org/keywords/graph-isomorphism","display_name":"Graph isomorphism","score":0.547829806804657},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.48328641057014465},{"id":"https://openalex.org/keywords/clique-width","display_name":"Clique-width","score":0.4519325792789459},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4433937668800354},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.43592825531959534},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41472315788269043},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.40342432260513306},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.333410382270813},{"id":"https://openalex.org/keywords/voltage-graph","display_name":"Voltage graph","score":0.32300400733947754},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25897371768951416},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.2212314009666443}],"concepts":[{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.8421613574028015},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6432463526725769},{"id":"https://openalex.org/C61665672","wikidata":"https://www.wikidata.org/wiki/Q303100","display_name":"Graph isomorphism","level":4,"score":0.547829806804657},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.48328641057014465},{"id":"https://openalex.org/C5737132","wikidata":"https://www.wikidata.org/wiki/Q1101814","display_name":"Clique-width","level":5,"score":0.4519325792789459},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4433937668800354},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.43592825531959534},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41472315788269043},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.40342432260513306},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.333410382270813},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.32300400733947754},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25897371768951416},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.2212314009666443},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/sym16121631","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym16121631","pdf_url":"https://www.mdpi.com/2073-8994/16/12/1631/pdf?version=1733739096","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:4f348cd1241943a0b41f860a5384b04a","is_oa":false,"landing_page_url":"https://doaj.org/article/4f348cd1241943a0b41f860a5384b04a","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry, Vol 16, Iss 12, p 1631 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/sym16121631","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym16121631","pdf_url":"https://www.mdpi.com/2073-8994/16/12/1631/pdf?version=1733739096","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4405193820.pdf","grobid_xml":"https://content.openalex.org/works/W4405193820.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1484040084","https://openalex.org/W1938135513","https://openalex.org/W2150593711","https://openalex.org/W2157529519","https://openalex.org/W2222512263","https://openalex.org/W2624431344","https://openalex.org/W2952099486","https://openalex.org/W2972872749","https://openalex.org/W3090369187","https://openalex.org/W3131513104","https://openalex.org/W3135294327","https://openalex.org/W3173151551","https://openalex.org/W3181036294","https://openalex.org/W4233756358","https://openalex.org/W4238762626","https://openalex.org/W4240416043","https://openalex.org/W4254751698","https://openalex.org/W4306405914","https://openalex.org/W4313366927","https://openalex.org/W4382568112","https://openalex.org/W4388092707","https://openalex.org/W4388524030","https://openalex.org/W4402193767","https://openalex.org/W6746912576","https://openalex.org/W6756040250","https://openalex.org/W6764969287","https://openalex.org/W6772452955","https://openalex.org/W6797132756","https://openalex.org/W6848586902","https://openalex.org/W6854076163","https://openalex.org/W6858040470","https://openalex.org/W7024726955"],"related_works":["https://openalex.org/W2567825307","https://openalex.org/W1592682627","https://openalex.org/W4295762832","https://openalex.org/W2945016732","https://openalex.org/W2785998768","https://openalex.org/W2371352078","https://openalex.org/W2362975861","https://openalex.org/W2804963084","https://openalex.org/W4389544142","https://openalex.org/W2489339695"],"abstract_inverted_index":{"Solving":[0],"maximum":[1,181],"matching":[2,34,182],"problems":[3,35,183],"in":[4,9,77,93,184,212,223,239],"bipartite":[5,185,224],"graphs":[6],"is":[7],"critical":[8],"fields":[10],"such":[11,126,155],"as":[12,127,156],"computational":[13,58],"biology":[14],"and":[15,50,60,81,86,101,108,113,122,133,163,170,195,209,237,246],"social":[16],"network":[17],"analysis.":[18],"This":[19],"study":[20,201],"introduces":[21],"HybridGNN,":[22],"a":[23,40,189],"novel":[24],"Graph":[25,43,47,51,213],"Neural":[26],"Network":[27],"model":[28,61],"designed":[29],"to":[30,56,139,179,235],"efficiently":[31],"address":[32,231],"complex":[33,171,250],"at":[36],"scale.":[37],"HybridGNN":[38],"leverages":[39],"combination":[41],"of":[42,79,99,106,206,221,249],"Attention":[44],"Networks":[45,53],"(GATv2),":[46],"SAGE":[48],"(SAGEConv),":[49],"Isomorphism":[52],"(GIN)":[54],"layers":[55,88,103],"enhance":[57],"efficiency":[59],"performance.":[62,142],"Through":[63],"extensive":[64],"ablation":[65],"experiments,":[66],"we":[67,116,230],"identify":[68],"that":[69,150],"while":[70],"the":[71,97,157,160,164,204,207,219,232,244],"SAGEConv":[72],"layer":[73],"demonstrates":[74],"suboptimal":[75],"performance":[76],"terms":[78],"accuracy":[80,112],"F1-score,":[82],"configurations":[83,120],"incorporating":[84],"GATv2":[85,100],"GIN":[87,102],"show":[89],"significant":[90],"improvements.":[91],"Specifically,":[92],"six-layer":[94],"GNN":[95,119],"architectures,":[96],"combinations":[98],"with":[104,203],"ratios":[105],"4:2":[107],"5:1":[109],"yield":[110],"superior":[111],"F1-score.":[114],"Therefore,":[115],"name":[117],"these":[118],"HybridGNN1":[121],"HybridGNN2.":[123],"Additionally,":[124],"techniques":[125],"mixed":[128],"precision":[129],"training,":[130],"gradient":[131],"accumulation,":[132],"Jumping":[134],"Knowledge":[135],"networks":[136],"are":[137],"integrated":[138],"further":[140],"optimize":[141],"Evaluations":[143],"on":[144],"an":[145],"email":[146],"communication":[147],"dataset":[148],"reveal":[149],"HybridGNNs":[151],"outperform":[152],"traditional":[153],"algorithms":[154],"Hopcroft\u2013Karp":[158],"algorithm,":[159,162,166],"Hungarian":[161],"Blossom/Edmonds\u2019":[165],"particularly":[167],"for":[168,192],"large":[169],"graphs.":[172],"These":[173],"findings":[174],"highlight":[175],"HybridGNN\u2019s":[176],"robust":[177],"capability":[178],"solve":[180],"graphs,":[186],"making":[187],"it":[188],"powerful":[190],"tool":[191],"analyzing":[193],"large-scale":[194],"intricate":[196],"graph":[197,225,240],"data.":[198],"Furthermore,":[199],"our":[200],"aligns":[202],"goals":[205],"Symmetry":[208],"Asymmetry":[210],"Study":[211],"Theory":[214],"special":[215],"issue":[216],"by":[217],"exploring":[218],"role":[220],"symmetry":[222,236],"structures.":[226],"By":[227],"leveraging":[228],"GNNs,":[229],"challenges":[233],"related":[234],"asymmetry":[238],"properties,":[241],"thereby":[242],"improving":[243],"reliability":[245],"fault":[247],"tolerance":[248],"networks.":[251]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}