{"id":"https://openalex.org/W7137889100","doi":"https://doi.org/10.1609/aaai.v40i24.39096","title":"Towards Multiple Missing Values-resistant Unsupervised Graph Anomaly Detection","display_name":"Towards Multiple Missing Values-resistant Unsupervised Graph Anomaly Detection","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7137889100","doi":"https://doi.org/10.1609/aaai.v40i24.39096"},"language":null,"primary_location":{"id":"doi:10.1609/aaai.v40i24.39096","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i24.39096","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v40i24.39096","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129700530","display_name":"Jiazhen Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jiazhen Chen","raw_affiliation_strings":["University of Waterloo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062005737","display_name":"Xiuqin Liang","orcid":null},"institutions":[{"id":"https://openalex.org/I145325580","display_name":"Deloitte (United States)","ror":"https://ror.org/03xkm6e60","country_code":"US","type":"company","lineage":["https://openalex.org/I145325580","https://openalex.org/I4210139068"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiuqin Liang","raw_affiliation_strings":["Deloitte Consulting"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Deloitte Consulting","institution_ids":["https://openalex.org/I145325580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028372795","display_name":"Sichao Fu","orcid":"https://orcid.org/0000-0002-4363-1000"},"institutions":[{"id":"https://openalex.org/I4210157617","display_name":"Huazhong University of Science and Technology Hospital","ror":"https://ror.org/05f9vfg11","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210157617"]},{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]},{"id":"https://openalex.org/I93477617","display_name":"Huizhou University","ror":"https://ror.org/03q3s7962","country_code":"CN","type":"education","lineage":["https://openalex.org/I93477617"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sichao Fu","raw_affiliation_strings":["Huazhong University of Science and Technology\nGuizhou University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology\nGuizhou University","institution_ids":["https://openalex.org/I4210157617","https://openalex.org/I47720641","https://openalex.org/I93477617"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129692990","display_name":"Zheng Ma","orcid":null},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Zheng Ma","raw_affiliation_strings":["University of Waterloo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129698090","display_name":"Weihua Ou","orcid":null},"institutions":[{"id":"https://openalex.org/I154893126","display_name":"Guizhou Normal University","ror":"https://ror.org/02x1pa065","country_code":"CN","type":"education","lineage":["https://openalex.org/I154893126"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihua Ou","raw_affiliation_strings":["Guizhou Normal University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guizhou Normal University","institution_ids":["https://openalex.org/I154893126"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":21.2894,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.97627407,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"40","issue":"24","first_page":"20100","last_page":"20108"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.6431000232696533,"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":0.6431000232696533,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.19439999759197235,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.015799999237060547,"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/imputation","display_name":"Imputation (statistics)","score":0.7990999817848206},{"id":"https://openalex.org/keywords/missing-data","display_name":"Missing data","score":0.675599992275238},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6304000020027161},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5605000257492065},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4528999924659729},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.435699999332428},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4237000048160553}],"concepts":[{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.7990999817848206},{"id":"https://openalex.org/C9357733","wikidata":"https://www.wikidata.org/wiki/Q6878417","display_name":"Missing data","level":2,"score":0.675599992275238},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6304000020027161},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6251000165939331},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5605000257492065},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5432999730110168},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4528999924659729},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.435699999332428},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4237000048160553},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3824999928474426},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.3571000099182129},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.33709999918937683},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.30219998955726624},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.2980000078678131},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2924000024795532},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26489999890327454},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.251800000667572}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1609/aaai.v40i24.39096","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i24.39096","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i24.39096","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i24.39096","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7617263793945312,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Unsupervised":[0],"graph":[1,134],"anomaly":[2],"detection":[3,77,104],"(GAD)":[4],"has":[5],"received":[6],"increasing":[7],"attention":[8],"in":[9,45,91,138],"recent":[10],"years.":[11],"It":[12],"aims":[13],"to":[14,49,143,176],"identify":[15],"anomalous":[16,64],"data":[17],"patterns":[18],"using":[19],"only":[20],"unlabeled":[21],"node":[22,35,56,82,131,194],"information":[23],"from":[24,141],"graph-structured":[25],"data.":[26],"However,":[27],"prevailing":[28],"unsupervised":[29,115,218],"GAD":[30,116,219],"methods":[31,220],"typically":[32],"assume":[33],"complete":[34],"attributes":[36,83,132],"and":[37,84,133,152,189,196],"structural":[38],"information-a":[39],"condition":[40],"that":[41,67,101,127,160,202,213],"is":[42],"seldom":[43],"satisfied":[44],"real-world":[46],"scenarios":[47],"due":[48],"privacy":[50],"constraints,":[51],"collection":[52],"errors,":[53],"or":[54],"dynamic":[55],"arrivals.":[57],"Standard":[58],"imputation":[59,73,178],"strategies":[60],"risk":[61],"\"repairing\"":[62],"rare":[63],"nodes":[65,162],"so":[66],"they":[68],"appear":[69],"normal,":[70],"thereby":[71],"introducing":[72],"bias":[74],"into":[75,192],"the":[76,96,144,186,204],"process.":[78],"Moreover,":[79],"when":[80],"both":[81],"edges":[85],"are":[86,149],"missing":[87,130,225],"simultaneously,":[88],"estimation":[89],"errors":[90,137],"one":[92,139],"view":[93,140],"can":[94],"contaminate":[95],"other,":[97],"causing":[98],"cross-view":[99],"interference":[100],"further":[102],"degrades":[103],"performance.":[105],"To":[106],"address":[107],"these":[108],"challenges,":[109],"we":[110,122,180],"propose":[111],"M\u00b2V-UGAD,":[112],"a":[113,124,155,164,222],"multiple-missing-values-resistant":[114],"framework":[117],"for":[118],"incomplete":[119],"graphs.":[120],"Specifically,":[121],"introduce":[123],"dual-pathway":[125],"encoder":[126],"independently":[128],"reconstructs":[129],"structure,":[135],"preventing":[136],"propagating":[142],"other.":[145],"The":[146],"two":[147],"pathways":[148],"then":[150],"fused":[151],"regularized":[153],"within":[154],"joint":[156],"latent":[157,182],"space":[158],"such":[159],"normal":[161,187],"occupy":[163],"compact":[165],"inner":[166],"manifold":[167],"while":[168],"anomalies":[169],"lie":[170],"on":[171,208],"an":[172],"outer":[173],"shell.":[174],"Finally,":[175],"mitigate":[177],"bias,":[179],"sample":[181],"codes":[183],"just":[184],"outside":[185],"region":[188],"decode":[190],"them":[191],"realistic":[193],"features":[195],"subgraphs,":[197],"yielding":[198],"hard":[199],"negative":[200],"examples":[201],"sharpen":[203],"decision":[205],"boundary.":[206],"Experiments":[207],"seven":[209],"public":[210],"benchmarks":[211],"show":[212],"M\u00b2V-UGAD":[214],"consistently":[215],"outperforms":[216],"existing":[217],"across":[221],"range":[223],"of":[224],"rates.":[226]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2026-03-18T00:00:00"}
