{"id":"https://openalex.org/W3193346003","doi":"https://doi.org/10.1109/tkde.2021.3103193","title":"Adversarial Representation Mechanism Learning for Network Embedding","display_name":"Adversarial Representation Mechanism Learning for Network Embedding","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3193346003","doi":"https://doi.org/10.1109/tkde.2021.3103193","mag":"3193346003"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2021.3103193","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3103193","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/A5009013876","display_name":"Dongxiao He","orcid":"https://orcid.org/0000-0002-1915-4179"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dongxiao He","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100453521","display_name":"Tao Wang","orcid":"https://orcid.org/0000-0002-4182-3586"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Wang","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003616481","display_name":"Lu Zhai","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lu Zhai","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012455357","display_name":"Di Jin","orcid":"https://orcid.org/0000-0002-7445-9936"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Di Jin","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001633360","display_name":"Liangwei Yang","orcid":"https://orcid.org/0000-0001-5660-766X"},"institutions":[{"id":"https://openalex.org/I184843921","display_name":"Hebei University of Technology","ror":"https://ror.org/018hded08","country_code":"CN","type":"education","lineage":["https://openalex.org/I184843921"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Yang","raw_affiliation_strings":["School of Artificial Intelligence, Hebei University of Technology, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Hebei University of Technology, Tianjin, China","institution_ids":["https://openalex.org/I184843921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103195106","display_name":"Yuxiao Huang","orcid":"https://orcid.org/0000-0001-9394-805X"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuxiao Huang","raw_affiliation_strings":["Data Science, George Washington University, Washington, D.C., USA"],"affiliations":[{"raw_affiliation_string":"Data Science, George Washington University, Washington, D.C., USA","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100736532","display_name":"Zhiyong Feng","orcid":"https://orcid.org/0000-0001-8158-7453"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyong Feng","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036357902","display_name":"Philip S. Yu","orcid":"https://orcid.org/0000-0002-3491-5968"},"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"]},{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Philip Yu","raw_affiliation_strings":["Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA","Institute for Data Science, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]},{"raw_affiliation_string":"Institute for Data Science, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5009013876"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":1.9473,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.86762243,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9991999864578247,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9991999864578247,"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/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.98580002784729,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8072428703308105},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.5926840901374817},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.5433782339096069},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5314067006111145},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5245330929756165},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.49655967950820923},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.43564313650131226},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4277237355709076},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3382878303527832}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8072428703308105},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.5926840901374817},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.5433782339096069},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5314067006111145},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5245330929756165},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.49655967950820923},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.43564313650131226},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4277237355709076},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3382878303527832},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2021.3103193","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3103193","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":[{"score":0.6499999761581421,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G6134627929","display_name":null,"funder_award_id":"61832014","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G678178878","display_name":null,"funder_award_id":"61876128","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8451749416","display_name":null,"funder_award_id":"61772361","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1888005072","https://openalex.org/W2010187764","https://openalex.org/W2019786737","https://openalex.org/W2060300932","https://openalex.org/W2090891622","https://openalex.org/W2099471712","https://openalex.org/W2104819583","https://openalex.org/W2120043163","https://openalex.org/W2123838014","https://openalex.org/W2154053567","https://openalex.org/W2154851992","https://openalex.org/W2166944917","https://openalex.org/W2405933695","https://openalex.org/W2508137831","https://openalex.org/W2604942799","https://openalex.org/W2622489478","https://openalex.org/W2808409763","https://openalex.org/W2808987817","https://openalex.org/W2950352474","https://openalex.org/W2950723285","https://openalex.org/W2962756421","https://openalex.org/W2962904108","https://openalex.org/W2963169753","https://openalex.org/W2972209102","https://openalex.org/W2986864699","https://openalex.org/W2998336824","https://openalex.org/W3034658947","https://openalex.org/W3035305379","https://openalex.org/W3093766087","https://openalex.org/W3104097132","https://openalex.org/W3112131107","https://openalex.org/W3137331829","https://openalex.org/W3173185686","https://openalex.org/W4243316134","https://openalex.org/W6690230747","https://openalex.org/W6715501732","https://openalex.org/W6717434760","https://openalex.org/W6726873649","https://openalex.org/W6730084236","https://openalex.org/W6731976766","https://openalex.org/W6732461846","https://openalex.org/W6747837047","https://openalex.org/W6755573351"],"related_works":["https://openalex.org/W2335364074","https://openalex.org/W4300480195","https://openalex.org/W4285606578","https://openalex.org/W2938696877","https://openalex.org/W3126201013","https://openalex.org/W4286796787","https://openalex.org/W4310745021","https://openalex.org/W4205395213","https://openalex.org/W2912933387","https://openalex.org/W2343431530"],"abstract_inverted_index":{"Network":[0],"embedding":[1,25],"which":[2,61,129,185,254],"is":[3,182,255],"to":[4,50,65,105,155,174,205,218,221],"learn":[5,51,156],"a":[6,13,52,56,117,202,223,231],"low":[7],"dimensional":[8],"representation":[9,69,83,88,137,141,159,177,188,225],"of":[10,97,101,108,123,190,195,233,272],"nodes":[11],"in":[12,18],"network":[14,20,24,59,127],"has":[15],"been":[16,41],"used":[17],"many":[19],"analysis":[21],"tasks.":[22],"Some":[23],"methods,":[26],"including":[27,235],"those":[28],"based":[29],"on":[30,81,87,135,230,261],"Generative":[31],"Adversarial":[32,140],"Networks":[33],"(GAN)":[34],"(a":[35],"promising":[36],"deep":[37],"learning":[38,79,120,133],"model),":[39],"have":[40],"proposed":[42],"recently.":[43],"Existing":[44],"GAN-based":[45],"methods":[46,251],"typically":[47],"use":[48,96],"GAN":[49,143],"Gaussian":[53,71],"distribution":[54],"as":[55],"prior":[57],"for":[58,126,257],"embedding,":[60,128],"makes":[62],"it":[63,91],"difficult":[64],"distinguish":[66],"the":[67,77,82,98,109,131,136,146,183,187,191,196,210,215,219,269,275],"node":[68,236,238],"from":[70,193,209],"distribution.":[72],"It":[73],"did":[74],"not":[75,93],"apply":[76],"adversarial":[78,119,132],"strategy":[80,134,204],"mechanism":[84,142,189],"but":[85],"just":[86],"results.":[89],"Thus,":[90],"does":[92],"make":[94],"full":[95],"essential":[99],"advantage":[100],"GAN,":[102],"and":[103,152,213,242],"leads":[104],"compromised":[106],"performance":[107],"method.":[110],"To":[111],"address":[112],"this":[113],"problem,":[114],"we":[115,200,245],"propose":[116],"novel":[118],"framework":[121],"consisting":[122],"three":[124],"players":[125],"applies":[130],"mechanism,":[138],"called":[139],"(ArmGAN).":[144],"Specifically,":[145],"first":[147],"two":[148,157,162],"players,":[149],"named":[150],"encoder":[151,192],"competitor,":[153],"aim":[154],"different":[158],"mechanisms":[160],"(i.e.,":[161],"ways":[163],"projecting":[164],"data":[165],"onto":[166],"latent":[167],"space).":[168],"They":[169],"compete":[170],"with":[171,248],"each":[172],"other":[173],"improve":[175],"their":[176],"mechanisms.":[178],"The":[179,265],"third":[180],"player":[181],"discriminator,":[184],"discriminate":[186],"that":[194],"competitor.":[197],"In":[198],"addition,":[199],"design":[201],"perturbation":[203],"produce":[206],"fake":[207,216],"networks":[208,217],"original":[211],"network,":[212],"feed":[214],"competitor":[220],"obtain":[222],"\u201cfake\u201d":[224],"mechanism.":[226],"We":[227],"evaluated":[228],"ArmGAN":[229,247,273],"variety":[232],"tasks":[234],"clustering,":[237],"classification,":[239],"link":[240],"prediction":[241],"visualization.":[243],"Moreover,":[244],"compared":[246],"10":[249],"state-of-the-art":[250],"(including":[252],"DGI,":[253],"well-known":[256],"its":[258],"high":[259],"accuracy)":[260],"7":[262],"real-world":[263],"networks.":[264],"experimental":[266],"results":[267],"show":[268],"significant":[270],"superiority":[271],"over":[274],"existing":[276],"methods.":[277]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}