{"id":"https://openalex.org/W3216736657","doi":"https://doi.org/10.1109/isi53945.2021.9624788","title":"Boosting Hidden Graph Node Classification for Large Social Networks","display_name":"Boosting Hidden Graph Node Classification for Large Social Networks","publication_year":2021,"publication_date":"2021-11-02","ids":{"openalex":"https://openalex.org/W3216736657","doi":"https://doi.org/10.1109/isi53945.2021.9624788","mag":"3216736657"},"language":"en","primary_location":{"id":"doi:10.1109/isi53945.2021.9624788","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isi53945.2021.9624788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Intelligence and Security Informatics (ISI)","raw_type":"proceedings-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/A5102609925","display_name":"Hanxuan Yang","orcid":"https://orcid.org/0000-0002-4473-2356"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hanxuan Yang","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China","University of Chinese Academy of Sciences, Beijing 100049, China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing 100049, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034695084","display_name":"Qingchao Kong","orcid":"https://orcid.org/0000-0002-1929-8404"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingchao Kong","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China","University of Chinese Academy of Sciences, Beijing 100049, China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing 100049, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035983004","display_name":"Wenji Mao","orcid":"https://orcid.org/0000-0003-2323-5091"},"institutions":[{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenji Mao","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China","University of Chinese Academy of Sciences, Beijing 100049, China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]},{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing 100049, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100435758","display_name":"Lei Wang","orcid":"https://orcid.org/0000-0001-6909-9561"},"institutions":[{"id":"https://openalex.org/I4210087772","display_name":"National Computer Network Emergency Response Technical Team/Coordination Center of Chinar","ror":"https://ror.org/00247dh76","country_code":"CN","type":"nonprofit","lineage":["https://openalex.org/I4210087772"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Wang","raw_affiliation_strings":["CNCERT/CC"],"affiliations":[{"raw_affiliation_string":"CNCERT/CC","institution_ids":["https://openalex.org/I4210087772"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102609925"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210094879","https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":0.2719,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.64677006,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9962000250816345,"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/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9919000267982483,"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":0.723997950553894},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5530369281768799},{"id":"https://openalex.org/keywords/unobservable","display_name":"Unobservable","score":0.49073779582977295},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.45995843410491943},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.4570702314376831},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4288291931152344},{"id":"https://openalex.org/keywords/hidden-node-problem","display_name":"Hidden node problem","score":0.4132803678512573},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39473992586135864},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.39027339220046997},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.37322017550468445},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10464620590209961}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.723997950553894},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5530369281768799},{"id":"https://openalex.org/C2780695315","wikidata":"https://www.wikidata.org/wiki/Q3799040","display_name":"Unobservable","level":2,"score":0.49073779582977295},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.45995843410491943},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.4570702314376831},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4288291931152344},{"id":"https://openalex.org/C156738730","wikidata":"https://www.wikidata.org/wiki/Q2565413","display_name":"Hidden node problem","level":5,"score":0.4132803678512573},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39473992586135864},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.39027339220046997},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.37322017550468445},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10464620590209961},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.0},{"id":"https://openalex.org/C152153834","wikidata":"https://www.wikidata.org/wiki/Q1339878","display_name":"Wi-Fi array","level":4,"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/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/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isi53945.2021.9624788","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isi53945.2021.9624788","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Intelligence and Security Informatics (ISI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309618","display_name":"Ministry of Science and Technology","ror":"https://ror.org/02b207r52"},{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1854214752","https://openalex.org/W1959608418","https://openalex.org/W2045021315","https://openalex.org/W2049607688","https://openalex.org/W2106650313","https://openalex.org/W2132513611","https://openalex.org/W2154851992","https://openalex.org/W2165874743","https://openalex.org/W2961295589","https://openalex.org/W2962756421","https://openalex.org/W2964015378","https://openalex.org/W2972057082","https://openalex.org/W2976859544","https://openalex.org/W2997223565","https://openalex.org/W3041956526","https://openalex.org/W3104097132","https://openalex.org/W3111938280","https://openalex.org/W3112475728","https://openalex.org/W3153329411","https://openalex.org/W4288276219","https://openalex.org/W4294558607","https://openalex.org/W4295177495","https://openalex.org/W4297733535","https://openalex.org/W4299281608","https://openalex.org/W4301874503","https://openalex.org/W4322614756","https://openalex.org/W6631190155","https://openalex.org/W6639055396","https://openalex.org/W6640963894","https://openalex.org/W6642674909","https://openalex.org/W6684578312","https://openalex.org/W6726873649","https://openalex.org/W6730084236","https://openalex.org/W6738964360","https://openalex.org/W6750392246","https://openalex.org/W6762759627","https://openalex.org/W6765543928","https://openalex.org/W6766612752","https://openalex.org/W6780593937"],"related_works":["https://openalex.org/W2614563012","https://openalex.org/W4293337373","https://openalex.org/W1968533609","https://openalex.org/W1984270607","https://openalex.org/W2151842462","https://openalex.org/W2295679373","https://openalex.org/W2891286602","https://openalex.org/W309851029","https://openalex.org/W1700370662","https://openalex.org/W1998320279"],"abstract_inverted_index":{"Identifying":[0],"hidden":[1,34,104,121,212],"nodes":[2,24,35,105],"in":[3,10,49,90],"social":[4,195],"networks":[5],"is":[6,28,191],"a":[7,126,137,160,173],"critical":[8],"issue":[9],"security-related":[11],"applications.":[12],"In":[13,95],"contrast":[14],"to":[15,31,64,73,142,152,162,193],"the":[16,33,40,46,75,97,108,113,118,144,155,167,206],"conventional":[17],"node":[18,56,66,84,122,163,169,178,214],"classification":[19,57],"on":[20,83,131,200],"graphs":[21],"with":[22],"all":[23],"being":[25],"observable,":[26],"it":[27],"more":[29],"challenging":[30],"classify":[32],"that":[36],"are":[37,71],"unobservable":[38],"during":[39],"training":[41],"process,":[42],"also":[43],"known":[44],"as":[45,159],"\u201cinductive":[47],"learning\u201d":[48],"previous":[50],"research.":[51],"Existing":[52],"approaches":[53],"for":[54,211],"inductive":[55],"mainly":[58],"adopt":[59],"graph":[60,100,139,156,213],"neural":[61,140],"network":[62,141],"models":[63],"learn":[65],"representations.":[67],"Although":[68],"these":[69],"methods":[70],"advantageous":[72],"modeling":[74],"topology":[76],"of":[77,120,148,208],"graph-structured":[78],"data,":[79],"they":[80],"rely":[81],"heavily":[82],"features":[85],"which":[86],"may":[87,106],"vary":[88],"significantly":[89],"different":[91],"specific":[92],"application":[93],"scenarios.":[94],"addition,":[96],"inherently":[98],"changeable":[99],"structure":[101,157],"induced":[102],"by":[103,187],"cause":[107],"over-fitting":[109],"problem.":[110],"To":[111],"address":[112],"above":[114],"issues":[115],"and":[116,171,189,204],"boost":[117],"performances":[119],"classification,":[123],"we":[124,135,165],"propose":[125],"deep":[127],"generative":[128],"model":[129,183],"based":[130],"variational":[132],"auto-encoders.":[133],"Specifically,":[134],"design":[136],"novel":[138],"aggregate":[143],"multi-hop":[145],"neighbor":[146],"information":[147,158],"each":[149],"node.":[150],"Meanwhile,":[151],"better":[153],"utilize":[154],"supplement":[161],"features,":[164],"consider":[166],"heterogeneous":[168],"influences":[170],"introduce":[172],"gated":[174],"attention":[175],"mechanism":[176],"using":[177],"degrees.":[179],"Moreover,":[180],"our":[181,209],"proposed":[182],"can":[184],"be":[185],"trained":[186],"minibatches":[188],"thus":[190],"applicable":[192],"large":[194],"networks.":[196],"We":[197],"conduct":[198],"experiments":[199],"four":[201],"real-world":[202],"datasets,":[203],"verify":[205],"effectiveness":[207],"method":[210],"classification.":[215]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
