{"id":"https://openalex.org/W4416223394","doi":"https://doi.org/10.3390/info16110985","title":"Graph Anomaly Detection Algorithm Based on Multi-View Heterogeneity Resistant Network","display_name":"Graph Anomaly Detection Algorithm Based on Multi-View Heterogeneity Resistant Network","publication_year":2025,"publication_date":"2025-11-14","ids":{"openalex":"https://openalex.org/W4416223394","doi":"https://doi.org/10.3390/info16110985"},"language":"en","primary_location":{"id":"doi:10.3390/info16110985","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16110985","pdf_url":"https://www.mdpi.com/2078-2489/16/11/985/pdf?version=1763112871","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2078-2489/16/11/985/pdf?version=1763112871","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010098036","display_name":"Yangrui Fan","orcid":"https://orcid.org/0000-0001-5356-7957"},"institutions":[{"id":"https://openalex.org/I174104030","display_name":"Taiyuan Normal University","ror":"https://ror.org/051k00p03","country_code":"CN","type":"education","lineage":["https://openalex.org/I174104030"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yangrui Fan","raw_affiliation_strings":["School of Computer Science and Technology, Taiyuan Normal University, Jinzhong 030619, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Taiyuan Normal University, Jinzhong 030619, China","institution_ids":["https://openalex.org/I174104030"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000861132","display_name":"Caixia Cui","orcid":"https://orcid.org/0000-0002-4466-8446"},"institutions":[{"id":"https://openalex.org/I174104030","display_name":"Taiyuan Normal University","ror":"https://ror.org/051k00p03","country_code":"CN","type":"education","lineage":["https://openalex.org/I174104030"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Caixia Cui","raw_affiliation_strings":["School of Computer Science and Technology, Taiyuan Normal University, Jinzhong 030619, China"],"raw_orcid":"https://orcid.org/0000-0002-4466-8446","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Taiyuan Normal University, Jinzhong 030619, China","institution_ids":["https://openalex.org/I174104030"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100404740","display_name":"Zhiqiang Wang","orcid":"https://orcid.org/0000-0002-9269-3988"},"institutions":[{"id":"https://openalex.org/I181877577","display_name":"Shanxi University","ror":"https://ror.org/03y3e3s17","country_code":"CN","type":"education","lineage":["https://openalex.org/I181877577"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqiang Wang","raw_affiliation_strings":["School of Computer and Information Technology, Shanxi University, Taiyuan 030006, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology, Shanxi University, Taiyuan 030006, China","institution_ids":["https://openalex.org/I181877577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052030057","display_name":"Hui Qi","orcid":"https://orcid.org/0000-0002-9930-9088"},"institutions":[{"id":"https://openalex.org/I174104030","display_name":"Taiyuan Normal University","ror":"https://ror.org/051k00p03","country_code":"CN","type":"education","lineage":["https://openalex.org/I174104030"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hui Qi","raw_affiliation_strings":["School of Computer Science and Technology, Taiyuan Normal University, Jinzhong 030619, China"],"raw_orcid":"https://orcid.org/0000-0002-9930-9088","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Taiyuan Normal University, Jinzhong 030619, China","institution_ids":["https://openalex.org/I174104030"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101311536","display_name":"Zhen Tian","orcid":"https://orcid.org/0009-0009-2962-6334"},"institutions":[{"id":"https://openalex.org/I7882870","display_name":"University of Glasgow","ror":"https://ror.org/00vtgdb53","country_code":"GB","type":"education","lineage":["https://openalex.org/I7882870"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Zhen Tian","raw_affiliation_strings":["James att School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK"],"raw_orcid":"https://orcid.org/0009-0009-2962-6334","affiliations":[{"raw_affiliation_string":"James att School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK","institution_ids":["https://openalex.org/I7882870"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5000861132"],"corresponding_institution_ids":["https://openalex.org/I174104030"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":1.396,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.8709427,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"16","issue":"11","first_page":"985","last_page":"985"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.8996999859809875,"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":0.8996999859809875,"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":0.011099999770522118,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.009700000286102295,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5658000111579895},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5130000114440918},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4966999888420105},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.4966999888420105},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46650001406669617},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.4634999930858612},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.4530999958515167},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.39879998564720154}],"concepts":[{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5658000111579895},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5490000247955322},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5130000114440918},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.4966999888420105},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4966999888420105},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.47870001196861267},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46650001406669617},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.4634999930858612},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4530999958515167},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4408999979496002},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43799999356269836},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.39879998564720154},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.38909998536109924},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.3544999957084656},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.3386000096797943},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.335099995136261},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.3343999981880188},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.3336000144481659},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.2906000018119812},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2809999883174896},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.27880001068115234},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2705000042915344},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.2702000141143799},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.26980000734329224}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/info16110985","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16110985","pdf_url":"https://www.mdpi.com/2078-2489/16/11/985/pdf?version=1763112871","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},{"id":"pmh:oai:eprints.gla.ac.uk:371755","is_oa":true,"landing_page_url":"https://eprints.gla.ac.uk/view/author/60447.html>","pdf_url":null,"source":{"id":"https://openalex.org/S4210235606","display_name":"ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam)","issn_l":"2622-8912","issn":["2622-8912","2622-8920"],"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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Articles"},{"id":"pmh:oai:doaj.org/article:de48af2279ca48a18390035e9b7c10fd","is_oa":true,"landing_page_url":"https://doaj.org/article/de48af2279ca48a18390035e9b7c10fd","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Information, Vol 16, Iss 11, p 985 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/info16110985","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16110985","pdf_url":"https://www.mdpi.com/2078-2489/16/11/985/pdf?version=1763112871","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Information","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4258773358","display_name":null,"funder_award_id":"62272285","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":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416223394.pdf","grobid_xml":"https://content.openalex.org/works/W4416223394.grobid-xml"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W3068123808","https://openalex.org/W3080922200","https://openalex.org/W3090999459","https://openalex.org/W3126928293","https://openalex.org/W3153858161","https://openalex.org/W3169637772","https://openalex.org/W3198839083","https://openalex.org/W4221101570","https://openalex.org/W4224319742","https://openalex.org/W4367047347","https://openalex.org/W4382239148","https://openalex.org/W4384789817","https://openalex.org/W4393153310","https://openalex.org/W4401845336","https://openalex.org/W4402170787","https://openalex.org/W4410001068"],"related_works":[],"abstract_inverted_index":{"Graph":[0],"anomaly":[1],"detection":[2],"(GAD)":[3],"aims":[4],"to":[5,24,51,85,113,143],"identify":[6],"nodes":[7],"or":[8],"edges":[9,20,46],"that":[10,169],"deviate":[11],"from":[12,118,135],"normal":[13],"patterns.":[14],"However,":[15],"the":[16,35,53,59,67,79,87,115,132,136,145,170,179,184,197,200],"presence":[17],"of":[18,56,81,89,147,199],"heterophilic":[19,45,90,110,157],"in":[21,150,191],"graphs":[22],"leads":[23],"feature":[25,122,153],"over-smoothing":[26],"issues.":[27],"To":[28],"overcome":[29],"this":[30,32],"limitation,":[31],"paper":[33],"proposes":[34],"multi-view":[36,48,202],"heterogeneity":[37],"resistant":[38],"network":[39],"(MV-GHRN)":[40],"model,":[41],"which":[42],"progressively":[43],"purifies":[44],"through":[47],"collaboration.":[49],"First,":[50],"address":[52],"noise":[54],"sensitivity":[55],"single":[57],"predictions,":[58],"method":[60],"computes":[61],"post-aggregation":[62],"(PA)":[63],"scores":[64],"for":[65],"both":[66,106,119],"original":[68],"graph":[69,116],"and":[70,74,121,166,189,193],"its":[71],"perturbed":[72],"versions":[73],"performs":[75],"weighted":[76],"fusion,":[77],"leveraging":[78],"consistency":[80],"multiple":[82],"prediction":[83],"perspectives":[84],"enhance":[86],"reliability":[88],"edge":[91,111],"identification.":[92],"Second,":[93],"a":[94,101,125],"cosine":[95],"similarity":[96],"view":[97,149],"is":[98,129],"introduced":[99],"as":[100,140,164],"complementary":[102],"structural":[103],"perspective,":[104],"with":[105],"views":[107,139],"independently":[108],"completing":[109],"pruning":[112],"clean":[114],"structure":[117],"topological":[120],"dimensions.":[123],"Finally,":[124],"cross-view":[126],"self-distillation":[127],"mechanism":[128],"designed,":[130],"using":[131],"fused":[133],"predictions":[134],"two":[137],"purified":[138],"teacher":[141],"signals":[142],"guide":[144],"optimization":[146],"each":[148],"reverse,":[151],"correcting":[152],"biases":[154],"caused":[155],"by":[156,187],"edges.":[158],"Experiments":[159],"on":[160,178],"benchmark":[161],"datasets":[162],"such":[163],"YelpChi":[165,180],"Amazon":[167],"demonstrate":[168],"framework":[171],"significantly":[172],"outperforms":[173],"existing":[174],"methods.":[175],"For":[176],"instance,":[177],"dataset,":[181],"MV-GHRN":[182],"surpasses":[183],"best":[185],"baseline":[186],"16.8%":[188],"5.2%":[190],"F1-Macro":[192],"AUC,":[194],"respectively,":[195],"validating":[196],"effectiveness":[198],"progressive":[201],"purification":[203],"mechanism.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-11-14T00:00:00"}
