{"id":"https://openalex.org/W7133355394","doi":"https://doi.org/10.48550/arxiv.2603.01806","title":"GCTAM: Global and Contextual Truncated Affinity Combined Maximization Model For Unsupervised Graph Anomaly Detection","display_name":"GCTAM: Global and Contextual Truncated Affinity Combined Maximization Model For Unsupervised Graph Anomaly Detection","publication_year":2026,"publication_date":"2026-03-02","ids":{"openalex":"https://openalex.org/W7133355394","doi":"https://doi.org/10.48550/arxiv.2603.01806"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.01806","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01806","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.01806","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5127978719","display_name":"Xiong Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Xiong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128019659","display_name":"Hong Peng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Peng, Hong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127918772","display_name":"Zhenli He","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"He, Zhenli","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128005391","display_name":"Cheng Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Cheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128009214","display_name":"Xin Jin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Xin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5127972362","display_name":"Hua Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Hua","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.6894000172615051,"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":0.6894000172615051,"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":0.08229999989271164,"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/T12127","display_name":"Software System Performance and Reliability","score":0.038600001484155655,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/maximization","display_name":"Maximization","score":0.6317999958992004},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6061000227928162},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5889999866485596},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.5859000086784363},{"id":"https://openalex.org/keywords/truncation","display_name":"Truncation (statistics)","score":0.5539000034332275},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5192999839782715}],"concepts":[{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.6317999958992004},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6061000227928162},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5892999768257141},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5889999866485596},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.5859000086784363},{"id":"https://openalex.org/C106195933","wikidata":"https://www.wikidata.org/wiki/Q7847935","display_name":"Truncation (statistics)","level":2,"score":0.5539000034332275},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5192999839782715},{"id":"https://openalex.org/C2780283098","wikidata":"https://www.wikidata.org/wiki/Q4688960","display_name":"Affinities","level":2,"score":0.48089998960494995},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.45339998602867126},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.388700008392334},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32899999618530273},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.3237000107765198},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.32260000705718994},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3034999966621399},{"id":"https://openalex.org/C109659709","wikidata":"https://www.wikidata.org/wiki/Q3407504","display_name":"Affinity propagation","level":5,"score":0.30090001225471497},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2904999852180481}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.01806","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01806","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.01806","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.01806","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.5165034532546997}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Anomalies":[0],"often":[1],"occur":[2],"in":[3,18,168,189,202],"real-world":[4,159,192],"information":[5,44],"networks/graphs,":[6],"such":[7],"as":[8],"malevolent":[9],"users,":[10,14],"malicious":[11],"comments,":[12],"banned":[13],"and":[15,45,85,99,120,195,206,208],"fake":[16],"news":[17],"social":[19],"graphs.":[20],"The":[21,128],"latest":[22],"graph":[23,170],"anomaly":[24,38,106,171],"detection":[25,172],"methods":[26,72,167],"use":[27,136],"a":[28,78,114],"novel":[29,115],"mechanism":[30],"called":[31],"truncated":[32],"affinity":[33,122,142,151],"maximization":[34],"(TAM)":[35],"to":[36,65,77,123,135,139],"detect":[37],"nodes":[39,56,64,75],"without":[40],"using":[41],"any":[42],"label":[43],"achieve":[46],"impressive":[47],"results.":[48],"TAM":[49],"maximizes":[50],"the":[51,54,59,62,67,83,103,125,132,141,150,181,210,219],"affinities":[52,60,87],"among":[53],"normal":[55,98,153],"while":[57,146,213],"truncating":[58],"of":[61,88,105,131,143,152],"anomalous":[63,100,126,144],"identify":[66],"anomalies.":[68],"However,":[69],"existing":[70],"TAM-based":[71],"truncate":[73,124],"suspicious":[74],"according":[76],"rigid":[79],"threshold":[80],"that":[81,162],"ignores":[82],"specificity":[84],"high-order":[86],"different":[89],"nodes.":[90,127,154],"This":[91],"inevitably":[92],"causes":[93],"inefficient":[94],"truncations":[95],"from":[96],"both":[97],"nodes,":[101,145],"limiting":[102],"effectiveness":[104],"detection.":[107],"To":[108],"this":[109,111],"end,":[110],"paper":[112],"proposes":[113],"truncation":[116,138,148],"model":[117],"combining":[118],"contextual":[119,137],"global":[121,147],"core":[129],"idea":[130],"work":[133],"is":[134],"decrease":[140],"increases":[149],"Extensive":[155],"experiments":[156],"on":[157],"massive":[158],"datasets":[160],"show":[161],"our":[163,198],"method":[164,183,199],"surpasses":[165],"peer":[166],"most":[169,214],"tasks.":[173,220],"In":[174],"highlights,":[175],"compared":[176],"with":[177],"previous":[178,215],"state-of-the-art":[179],"methods,":[180],"proposed":[182],"has":[184],"+15\\%":[185],"$\\sim$":[186],"+20\\%":[187],"improvements":[188],"two":[190],"famous":[191],"datasets,":[193,204],"Amazon":[194],"YelpChi.":[196],"Notably,":[197],"works":[200],"well":[201],"large":[203],"Amazin-all":[205],"YelpChi-all,":[207],"achieves":[209],"best":[211],"results,":[212],"models":[216],"cannot":[217],"complete":[218]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-04T00:00:00"}