{"id":"https://openalex.org/W4205694765","doi":"https://doi.org/10.1109/access.2022.3144233","title":"Motif-Aware Adversarial Graph Representation Learning","display_name":"Motif-Aware Adversarial Graph Representation Learning","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4205694765","doi":"https://doi.org/10.1109/access.2022.3144233"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3144233","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3144233","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09684408.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09684408.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043265173","display_name":"Ming Zhao","orcid":"https://orcid.org/0000-0002-1470-7678"},"institutions":[{"id":"https://openalex.org/I9356336","display_name":"Zhangzhou Normal University","ror":"https://ror.org/02vj1vm13","country_code":"CN","type":"education","lineage":["https://openalex.org/I9356336"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ming Zhao","raw_affiliation_strings":["Fujian Key Laboratory of Granular Computing and Application, Minnan Normal University, Zhangzhou, China"],"affiliations":[{"raw_affiliation_string":"Fujian Key Laboratory of Granular Computing and Application, Minnan Normal University, Zhangzhou, China","institution_ids":["https://openalex.org/I9356336"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071742844","display_name":"Yinglong Zhang","orcid":"https://orcid.org/0000-0002-3293-3257"},"institutions":[{"id":"https://openalex.org/I9356336","display_name":"Zhangzhou Normal University","ror":"https://ror.org/02vj1vm13","country_code":"CN","type":"education","lineage":["https://openalex.org/I9356336"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yinglong Zhang","raw_affiliation_strings":["School of Physics and Information Engineering, Minnan Normal University, Zhangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Physics and Information Engineering, Minnan Normal University, Zhangzhou, China","institution_ids":["https://openalex.org/I9356336"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006869135","display_name":"Xuewen Xia","orcid":"https://orcid.org/0000-0002-4938-1479"},"institutions":[{"id":"https://openalex.org/I9356336","display_name":"Zhangzhou Normal University","ror":"https://ror.org/02vj1vm13","country_code":"CN","type":"education","lineage":["https://openalex.org/I9356336"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuewen Xia","raw_affiliation_strings":["School of Physics and Information Engineering, Minnan Normal University, Zhangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Physics and Information Engineering, Minnan Normal University, Zhangzhou, China","institution_ids":["https://openalex.org/I9356336"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039477889","display_name":"Xing Xu","orcid":"https://orcid.org/0000-0003-4773-3263"},"institutions":[{"id":"https://openalex.org/I9356336","display_name":"Zhangzhou Normal University","ror":"https://ror.org/02vj1vm13","country_code":"CN","type":"education","lineage":["https://openalex.org/I9356336"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Xu","raw_affiliation_strings":["School of Physics and Information Engineering, Minnan Normal University, Zhangzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Physics and Information Engineering, Minnan Normal University, Zhangzhou, China","institution_ids":["https://openalex.org/I9356336"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5043265173"],"corresponding_institution_ids":["https://openalex.org/I9356336"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.4134,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.65998003,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"10","issue":null,"first_page":"8617","last_page":"8626"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9977999925613403,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9973999857902527,"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/adversarial-system","display_name":"Adversarial system","score":0.7612824440002441},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6697161197662354},{"id":"https://openalex.org/keywords/motif","display_name":"Motif (music)","score":0.5505516529083252},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4818469285964966},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.45507657527923584},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.43861281871795654}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7612824440002441},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6697161197662354},{"id":"https://openalex.org/C32276052","wikidata":"https://www.wikidata.org/wiki/Q908349","display_name":"Motif (music)","level":2,"score":0.5505516529083252},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4818469285964966},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.45507657527923584},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.43861281871795654},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3144233","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3144233","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09684408.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:dac6af0d0be7438f98d8aeebfee720a4","is_oa":true,"landing_page_url":"https://doaj.org/article/dac6af0d0be7438f98d8aeebfee720a4","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 8617-8626 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3144233","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3144233","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9668973/09684408.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6700000166893005,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G16093760","display_name":null,"funder_award_id":"2021J011008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G228043642","display_name":null,"funder_award_id":"2021J01100","funder_id":"https://openalex.org/F4320321878","funder_display_name":"Natural Science Foundation of Fujian Province"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4055064482","display_name":null,"funder_award_id":"2021J011008","funder_id":"https://openalex.org/F4320321878","funder_display_name":"Natural Science Foundation of Fujian Province"},{"id":"https://openalex.org/G4542358678","display_name":null,"funder_award_id":"61762036","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5599936654","display_name":null,"funder_award_id":"KJ19009","funder_id":"https://openalex.org/F4320324314","funder_display_name":"Minnan Normal University"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6883457225","display_name":null,"funder_award_id":"2021J011007","funder_id":"https://openalex.org/F4320321878","funder_display_name":"Natural Science Foundation of Fujian Province"},{"id":"https://openalex.org/G975385493","display_name":null,"funder_award_id":"2021J011007","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"},{"id":"https://openalex.org/F4320321878","display_name":"Natural Science Foundation of Fujian Province","ror":null},{"id":"https://openalex.org/F4320324314","display_name":"Minnan Normal University","ror":"https://ror.org/02vj1vm13"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4205694765.pdf","grobid_xml":"https://content.openalex.org/works/W4205694765.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1888005072","https://openalex.org/W1976722121","https://openalex.org/W2019786737","https://openalex.org/W2046253692","https://openalex.org/W2062797058","https://openalex.org/W2074724691","https://openalex.org/W2090891622","https://openalex.org/W2135303340","https://openalex.org/W2153959628","https://openalex.org/W2154851992","https://openalex.org/W2156718197","https://openalex.org/W2187089797","https://openalex.org/W2387462954","https://openalex.org/W2393319904","https://openalex.org/W2405933695","https://openalex.org/W2415243320","https://openalex.org/W2508137831","https://openalex.org/W2585003791","https://openalex.org/W2604942799","https://openalex.org/W2770717124","https://openalex.org/W2808409763","https://openalex.org/W2890855364","https://openalex.org/W2898322439","https://openalex.org/W2927299114","https://openalex.org/W2950352474","https://openalex.org/W2962756421","https://openalex.org/W2965862227","https://openalex.org/W2971713442","https://openalex.org/W2998722865","https://openalex.org/W3034671692","https://openalex.org/W3080456792","https://openalex.org/W3096565974","https://openalex.org/W3096831136","https://openalex.org/W3104097132","https://openalex.org/W3109649745","https://openalex.org/W3172698735","https://openalex.org/W4297814305","https://openalex.org/W4322614756","https://openalex.org/W6629622578","https://openalex.org/W6631190155","https://openalex.org/W6699364125","https://openalex.org/W6726873649","https://openalex.org/W6730084236","https://openalex.org/W6737748565","https://openalex.org/W6746536644","https://openalex.org/W6758396028","https://openalex.org/W6786788534"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4310988119","https://openalex.org/W4285226279","https://openalex.org/W4288019534"],"abstract_inverted_index":{"Graph":[0],"representation":[1,79],"learning":[2],"has":[3,11,34,250],"been":[4,12],"extensively":[5],"studied":[6],"in":[7,15,145,254],"recent":[8],"years.":[9],"It":[10],"proven":[13],"effective":[14],"network":[16,33],"analysis":[17],"and":[18,25,93,200,237,262],"mining":[19],"tasks":[20],"such":[21],"as":[22],"node":[23,260],"classification":[24,261],"link":[26,258],"prediction.":[27],"Learning":[28],"method":[29],"based":[30,80],"on":[31,81,244],"neural":[32],"become":[35],"mainstream":[36],"solution":[37],"because":[38],"it":[39],"can":[40,235],"efficiently":[41],"preserve":[42,161],"nonlinear":[43],"characteristics":[44],"of":[45,127,164,174,196,218],"graph.":[46],"However,":[47],"more":[48],"efficient":[49],"ways":[50],"to":[51,76,131,157,160,181,205],"encode":[52],"complex":[53],"graph":[54,78,130],"structures":[55],"are":[56],"still":[57],"being":[58],"explored.":[59],"In":[60,230],"this":[61],"paper,":[62],"for":[63],"undirected":[64],"graphs,":[65],"we":[66,100,117,155,176],"present":[67],"a":[68,82,133,162,168,178],"novel":[69],"Motif-Aware":[70],"Generative":[71],"Adversarial":[72],"Network":[73],"(MotifGAN)":[74],"model":[75,180,193],"learn":[77],"re-weighted":[83],"graph,":[84],"which":[85,109],"unifies":[86],"both":[87,233],"the":[88,94,102,111,119,124,128,146,151,187,207,212,216,228],"Motif":[89,112],"higher":[90,113],"order":[91,97,114],"structure":[92,153,189],"original":[95,129],"lower":[96],"structure.":[98,115],"Firstly,":[99],"obtain":[101],"motif":[103,107,120,137,141,147,208],"adjacency":[104,121,125],"matrix":[105,122,126,135,149],"by":[106,171,227],"mining,":[108],"encodes":[110],"Then":[116],"couple":[118],"with":[123],"get":[132],"reweighted":[134],"named":[136],"connectivity":[138,142,148,209,217],"matrix.":[139],"The":[140,191],"distribution":[143],"implicit":[144],"is":[150,167,221],"target":[152,188],"information":[154,166],"need":[156],"preserve.":[158],"How":[159],"wealth":[163],"structural":[165],"challenge.":[169],"Inspired":[170],"related":[172],"applications":[173],"GAN,":[175],"formulate":[177],"GAN":[179,192],"generate":[182],"embedding":[183],"representations":[184],"that":[185,248],"satisfy":[186],"conditions.":[190],"usually":[194],"consists":[195],"two":[197,219],"components:":[198],"generator":[199,203],"discriminator.":[201],"Our":[202],"tries":[204],"approximate":[206],"distribution,":[210],"while":[211],"discriminator":[213],"detects":[214],"whether":[215],"vertexes":[220],"from":[222],"ground":[223],"truth":[224],"or":[225],"generated":[226],"generator.":[229],"adversarial":[231],"training,":[232],"parts":[234],"alternately":[236],"iteratively":[238],"boost":[239],"their":[240],"performance.":[241],"Experimental":[242],"results":[243],"public":[245],"datasets":[246],"show":[247],"MotifGAN":[249],"made":[251],"substantial":[252],"progress":[253],"various":[255],"applications,":[256],"including":[257],"prediction,":[259],"visualization.":[263]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}