{"id":"https://openalex.org/W4412877120","doi":"https://doi.org/10.1145/3711896.3736983","title":"Global Interpretable Graph-level Anomaly Detection via Prototype","display_name":"Global Interpretable Graph-level Anomaly Detection via Prototype","publication_year":2025,"publication_date":"2025-08-03","ids":{"openalex":"https://openalex.org/W4412877120","doi":"https://doi.org/10.1145/3711896.3736983"},"language":"en","primary_location":{"id":"doi:10.1145/3711896.3736983","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3736983","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3736983","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3736983","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100433327","display_name":"Zhenyu Yang","orcid":"https://orcid.org/0000-0002-6588-3014"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Zhenyu Yang","raw_affiliation_strings":["School of Computing, Macquarie University, Sydney, New South Wales, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computing, Macquarie University, Sydney, New South Wales, Australia","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066698067","display_name":"Ge Zhang","orcid":"https://orcid.org/0000-0001-6009-780X"},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ge Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Donghua University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Donghua University, Shanghai, China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007475662","display_name":"Jia Wu","orcid":"https://orcid.org/0000-0002-1371-5801"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jia Wu","raw_affiliation_strings":["School of Computing, Macquarie University, Sydney, New South Wales, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computing, Macquarie University, Sydney, New South Wales, Australia","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009644404","display_name":"Jian Yang","orcid":"https://orcid.org/0000-0002-4408-1952"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jian Yang","raw_affiliation_strings":["School of Computing, Macquarie University, Sydney, New South Wales, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computing, Macquarie University, Sydney, New South Wales, Australia","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101912402","display_name":"Shan Xue","orcid":"https://orcid.org/0000-0002-9123-5133"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Shan Xue","raw_affiliation_strings":["School of Computing, Macquarie University, Sydney, New South Wales, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computing, Macquarie University, Sydney, New South Wales, Australia","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056293251","display_name":"Amin Beheshti","orcid":"https://orcid.org/0000-0002-5988-5494"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Amin Beheshti","raw_affiliation_strings":["School of Computing, Macquarie University, Sydney, New South Wales, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computing, Macquarie University, Sydney, New South Wales, Australia","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100740622","display_name":"Hao Peng","orcid":"https://orcid.org/0000-0003-0458-5977"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Peng","raw_affiliation_strings":["School of Cyber Science and Technology, Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Cyber Science and Technology, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080744092","display_name":"Quan Z. Sheng","orcid":"https://orcid.org/0000-0002-3326-4147"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Quan Z. Sheng","raw_affiliation_strings":["School of Computing, Macquarie University, Sydney, New South Wales, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computing, Macquarie University, Sydney, New South Wales, Australia","institution_ids":["https://openalex.org/I99043593"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5100433327"],"corresponding_institution_ids":["https://openalex.org/I99043593"],"apc_list":null,"apc_paid":null,"fwci":4.9698,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.95120049,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3586","last_page":"3597"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.996399998664856,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.996399998664856,"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/T10028","display_name":"Topic Modeling","score":0.9754999876022339,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9706000089645386,"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/anomaly-detection","display_name":"Anomaly detection","score":0.7251640558242798},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6140491366386414},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.52391517162323},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.48999157547950745},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41407814621925354},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36045411229133606},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3418450951576233},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2126331329345703},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07074403762817383}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7251640558242798},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6140491366386414},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.52391517162323},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.48999157547950745},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41407814621925354},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36045411229133606},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3418450951576233},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2126331329345703},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07074403762817383},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3711896.3736983","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3736983","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3736983","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3711896.3736983","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3711896.3736983","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3711896.3736983","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.5299999713897705}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320591","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412877120.pdf","grobid_xml":"https://content.openalex.org/works/W4412877120.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W2056562706","https://openalex.org/W2173027866","https://openalex.org/W2519887557","https://openalex.org/W2551974706","https://openalex.org/W2557579533","https://openalex.org/W2624431344","https://openalex.org/W2788667846","https://openalex.org/W2788919350","https://openalex.org/W2949759968","https://openalex.org/W2962711740","https://openalex.org/W2964015378","https://openalex.org/W2964113829","https://openalex.org/W2979481854","https://openalex.org/W2994929655","https://openalex.org/W3035520720","https://openalex.org/W3035525394","https://openalex.org/W3035909655","https://openalex.org/W3103717137","https://openalex.org/W3114932221","https://openalex.org/W3126371003","https://openalex.org/W3163162581","https://openalex.org/W3166086511","https://openalex.org/W3214353465","https://openalex.org/W4213224406","https://openalex.org/W4221152136","https://openalex.org/W4285670757","https://openalex.org/W4290067549","https://openalex.org/W4293469690","https://openalex.org/W4294558607","https://openalex.org/W4297733535","https://openalex.org/W4302400283","https://openalex.org/W4320502379","https://openalex.org/W4321480062","https://openalex.org/W4383176294","https://openalex.org/W4385562644","https://openalex.org/W4386798100","https://openalex.org/W4387963933","https://openalex.org/W4388183174","https://openalex.org/W4392729268","https://openalex.org/W4401023722","https://openalex.org/W4402530312","https://openalex.org/W4403758858","https://openalex.org/W4404783049","https://openalex.org/W6601641200","https://openalex.org/W6745537798","https://openalex.org/W6754929296","https://openalex.org/W6762631216","https://openalex.org/W6762796984","https://openalex.org/W6786048916","https://openalex.org/W6809820091","https://openalex.org/W6869436318","https://openalex.org/W6874056255","https://openalex.org/W7037116381"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2667207928","https://openalex.org/W2912112202","https://openalex.org/W4377864969","https://openalex.org/W3120251014"],"abstract_inverted_index":{"Graph-level":[0],"anomaly":[1,163],"detection":[2,164],"(GLAD)":[3],"identifies":[4],"graphs":[5],"exhibiting":[6],"abnormal":[7],"properties":[8],"within":[9],"a":[10,72,133],"graph":[11],"dataset.Despite":[12],"promising":[13],"results":[14],"in":[15,27,162],"this":[16],"task,":[17],"the":[18,66,87,92,99,107,115,140,151,158,170,175],"state-of-the-art":[19],"methods":[20,38],"cannot":[21],"be":[22],"fully":[23],"trusted":[24],"and":[25,62,165],"deployed":[26],"realistic":[28],"scenarios":[29],"due":[30],"to":[31,40,60,64,113,138,179,183],"their":[32],"black-box":[33],"nature.To":[34],"alleviate":[35],"this,":[36],"existing":[37],"try":[39],"explain":[41],"predictions":[42],"by":[43],"extracting":[44],"important":[45],"subgraphs":[46,128],"from":[47,129,181],"each":[48],"graph,":[49],"as":[50,120],"instancelevel":[51],"explanations.However,":[52],"instance-level":[53],"explanations":[54,85,122,178],"across":[55],"all":[56],"samples":[57],"are":[58],"costly":[59],"verify":[61,180],"insufficient":[63],"capture":[65,114],"model's":[67,100],"general":[68],"behaviors.Thus,":[69],"we":[70,146],"propose":[71],"global":[73],"interpretable":[74],"Graph-Level":[75],"Anomaly":[76],"Detection":[77],"model":[78],"via":[79],"Prototype":[80],"(GLADPro),":[81],"which":[82],"provides":[83],"global-level":[84,121],"throughout":[86],"entire":[88],"dataset,":[89,172],"that":[90,96],"is,":[91],"significant":[93,117],"subgraph":[94,118],"patterns":[95,119],"consistently":[97],"influence":[98],"decisions.Specifically,":[101],"GLADPro":[102,161],"incorporates":[103],"prototype":[104],"learning":[105],"with":[106,126,143],"information":[108],"bottleneck":[109],"principle,":[110],"enabling":[111],"prototypes":[112,149],"most":[116],"through":[123],"persistent":[124],"interactions":[125],"key":[127],"input":[130],"graphs.In":[131],"addition,":[132],"regularization":[134],"term":[135],"is":[136],"proposed":[137],"prevent":[139],"collapse":[141],"traps":[142],"theoretical":[144],"proof.Finally,":[145],"filter":[147],"redundant":[148],"using":[150],"maximum":[152],"mean":[153],"discrepancy":[154],"metric.Extensive":[155],"experiments":[156],"demonstrate":[157],"superiority":[159],"of":[160,177],"explainability;":[166],"for":[167],"instance,":[168],"on":[169],"mutagen":[171],"it":[173],"reduces":[174],"number":[176],"1403":[182],"only":[184],"6.":[185]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
