{"id":"https://openalex.org/W4405844909","doi":"https://doi.org/10.1109/tnnls.2024.3519427","title":"HAGNN: Hybrid Aggregation for Heterogeneous Graph Neural Networks","display_name":"HAGNN: Hybrid Aggregation for Heterogeneous Graph Neural Networks","publication_year":2024,"publication_date":"2024-12-27","ids":{"openalex":"https://openalex.org/W4405844909","doi":"https://doi.org/10.1109/tnnls.2024.3519427","pmid":"https://pubmed.ncbi.nlm.nih.gov/40030810"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2024.3519427","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3519427","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/A5086985082","display_name":"Guanghui Zhu","orcid":"https://orcid.org/0000-0002-5069-5950"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanghui Zhu","raw_affiliation_strings":["State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-5069-5950","affiliations":[{"raw_affiliation_string":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110955965","display_name":"Zhennan Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhennan Zhu","raw_affiliation_strings":["State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hongyang Chen","orcid":"https://orcid.org/0000-0002-7626-0162"},"institutions":[{"id":"https://openalex.org/I4210123185","display_name":"Zhejiang Lab","ror":"https://ror.org/02m2h7991","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210123185"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongyang Chen","raw_affiliation_strings":["Research Center for Data Hub and Security, Zhejiang Lab, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-7626-0162","affiliations":[{"raw_affiliation_string":"Research Center for Data Hub and Security, Zhejiang Lab, Hangzhou, China","institution_ids":["https://openalex.org/I4210123185"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115598059","display_name":"Chunfeng Yuan","orcid":"https://orcid.org/0000-0002-8746-8137"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunfeng Yuan","raw_affiliation_strings":["State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-8746-8137","affiliations":[{"raw_affiliation_string":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046763264","display_name":"Yihua Huang","orcid":"https://orcid.org/0000-0003-1806-0936"},"institutions":[{"id":"https://openalex.org/I881766915","display_name":"Nanjing University","ror":"https://ror.org/01rxvg760","country_code":"CN","type":"education","lineage":["https://openalex.org/I881766915"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yihua Huang","raw_affiliation_strings":["State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0003-1806-0936","affiliations":[{"raw_affiliation_string":"State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China","institution_ids":["https://openalex.org/I881766915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.7234,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.95630632,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"36","issue":"8","first_page":"14536","last_page":"14550"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":1.0,"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":1.0,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9821000099182129,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9678999781608582,"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":0.8071615695953369},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6126297116279602},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5607481002807617},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4948346018791199},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.47869184613227844},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4559207558631897},{"id":"https://openalex.org/keywords/heterogeneous-network","display_name":"Heterogeneous network","score":0.4192083477973938},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2656240463256836},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.113628089427948}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8071615695953369},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6126297116279602},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5607481002807617},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4948346018791199},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.47869184613227844},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4559207558631897},{"id":"https://openalex.org/C158207573","wikidata":"https://www.wikidata.org/wiki/Q5747224","display_name":"Heterogeneous network","level":4,"score":0.4192083477973938},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2656240463256836},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.113628089427948},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","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/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2024.3519427","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2024.3519427","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:40030810","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40030810","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}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6824831872","display_name":null,"funder_award_id":"62102177","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320317102","display_name":"National Center of Science and Technology Evaluation","ror":null},{"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":63,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1556758605","https://openalex.org/W1888005072","https://openalex.org/W2131492273","https://openalex.org/W2153959628","https://openalex.org/W2154851992","https://openalex.org/W2187089797","https://openalex.org/W2244992438","https://openalex.org/W2604314403","https://openalex.org/W2607500032","https://openalex.org/W2735272571","https://openalex.org/W2743104969","https://openalex.org/W2767774008","https://openalex.org/W2907492528","https://openalex.org/W2911286998","https://openalex.org/W2945266622","https://openalex.org/W2962756421","https://openalex.org/W2964015378","https://openalex.org/W2965857891","https://openalex.org/W2997461192","https://openalex.org/W3003265726","https://openalex.org/W3004507689","https://openalex.org/W3012871709","https://openalex.org/W3103513278","https://openalex.org/W3104097132","https://openalex.org/W3108202858","https://openalex.org/W3116239416","https://openalex.org/W3155886566","https://openalex.org/W3164473340","https://openalex.org/W3167197358","https://openalex.org/W3172710079","https://openalex.org/W3176948526","https://openalex.org/W4223947193","https://openalex.org/W4224324119","https://openalex.org/W4225713789","https://openalex.org/W4226204438","https://openalex.org/W4252707176","https://openalex.org/W4282975557","https://openalex.org/W4283789866","https://openalex.org/W4285378361","https://openalex.org/W4289533954","https://openalex.org/W4297733535","https://openalex.org/W4306317244","https://openalex.org/W4367047306","https://openalex.org/W4382202833","https://openalex.org/W4385270111","https://openalex.org/W4385562708","https://openalex.org/W4387848991","https://openalex.org/W4390604335","https://openalex.org/W4391807422","https://openalex.org/W4392593816","https://openalex.org/W4392796768","https://openalex.org/W4400532713","https://openalex.org/W4405073635","https://openalex.org/W6631190155","https://openalex.org/W6690230747","https://openalex.org/W6738964360","https://openalex.org/W6767098714","https://openalex.org/W6772384842","https://openalex.org/W6786048916","https://openalex.org/W6803869602","https://openalex.org/W6810217773","https://openalex.org/W6810665001"],"related_works":["https://openalex.org/W1927327903","https://openalex.org/W1544665982","https://openalex.org/W2022479666","https://openalex.org/W2805504328","https://openalex.org/W4248847438","https://openalex.org/W2509090697","https://openalex.org/W1953159635","https://openalex.org/W4238131711","https://openalex.org/W3019690831","https://openalex.org/W1982097880"],"abstract_inverted_index":{"Heterogeneous":[0],"graph":[1,30,146],"neural":[2],"networks":[3],"(GNNs)":[4],"have":[5],"been":[6],"successful":[7],"in":[8,85,178],"handling":[9],"heterogeneous":[10,14,86,93,167,179],"graphs.":[11,180],"In":[12,49],"existing":[13,166,198],"GNNs,":[15],"meta-path":[16,34,104,145],"plays":[17],"an":[18],"essential":[19],"role.":[20],"However,":[21],"recent":[22],"work":[23],"pointed":[24],"out":[25],"that":[26,194],"a":[27,33,47,74,138,143],"simple":[28],"homogeneous":[29],"model":[31],"without":[32],"can":[35,171],"also":[36],"achieve":[37],"comparable":[38],"results,":[39],"which":[40],"calls":[41],"into":[42,121],"question":[43],"the":[44,55,79,103,107,117,132,158,176,197,201],"necessity":[45],"of":[46,82,98,175,205],"meta-path.":[48],"this":[50],"article,":[51],"we":[52,72,136,156],"first":[53],"present":[54],"intrinsic":[56],"difference":[57],"between":[58],"meta-path-based":[59,124],"and":[60,106,127,147,189,203],"meta-path-free":[61,128],"models,":[62,169],"i.e.,":[63],"how":[64],"to":[65,77,101],"select":[66],"neighbors":[67,105,110],"for":[68,92,112],"node":[69,113,185,187],"aggregation.":[70,130],"Then,":[71],"propose":[73,137],"novel":[75],"framework":[76],"utilize":[78],"rich":[80],"type":[81],"semantic":[83,150],"information":[84],"graphs":[87],"comprehensively,":[88],"namely,":[89],"hybrid":[90],"aggregation":[91,119,126,134,152],"GNNs":[94],"(HAGNNs).":[95],"The":[96],"core":[97],"HAGNN":[99,115,170,195],"is":[100],"leverage":[102],"directly":[108],"connected":[109],"simultaneously":[111],"aggregations.":[114],"divides":[116],"overall":[118],"process":[120],"two":[122],"phases:":[123],"intratype":[125,133],"intertype":[129],"During":[131],"phase,":[135],"new":[139],"data":[140],"structure":[141],"called":[142],"fused":[144],"perform":[148],"structural":[149],"aware":[151],"on":[153,184],"it.":[154],"Finally,":[155],"combine":[157],"embeddings":[159],"generated":[160],"by":[161],"each":[162],"phase.":[163],"Compared":[164],"with":[165],"GNN":[168],"take":[172],"full":[173],"advantage":[174],"heterogeneity":[177],"Extensive":[181],"experimental":[182],"results":[183],"classification,":[186],"clustering,":[188],"link":[190],"prediction":[191],"tasks":[192],"show":[193],"outperforms":[196],"modes,":[199],"demonstrating":[200],"effectiveness":[202],"efficiency":[204],"HAGNN.":[206]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}