{"id":"https://openalex.org/W7129596378","doi":"https://doi.org/10.1109/tkde.2026.3665892","title":"Explainable Anomaly Detection in Dynamic Heterogeneous Graphs via Relation Evolution","display_name":"Explainable Anomaly Detection in Dynamic Heterogeneous Graphs via Relation Evolution","publication_year":2026,"publication_date":"2026-02-17","ids":{"openalex":"https://openalex.org/W7129596378","doi":"https://doi.org/10.1109/tkde.2026.3665892"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2026.3665892","doi":"https://doi.org/10.1109/tkde.2026.3665892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2026.3665892","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","ccf-a","cwts-core","dongbi-a","fnege-3","jufo-3","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"},"volume":null,"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/A5035276090","display_name":"Xiaolin Han","orcid":"https://orcid.org/0000-0002-4347-1692","observed_orcids":["https://orcid.org/0000-0002-4347-1692"]},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolin Han","raw_affiliation_strings":["Northwestern Polytechnical University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0002-4347-1692","affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107701842","display_name":"Xiurui Hu","orcid":"https://orcid.org/0009-0008-1922-2443","observed_orcids":["https://orcid.org/0009-0008-1922-2443"]},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiurui Hu","raw_affiliation_strings":["Northwestern Polytechnical University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0009-0008-1922-2443","affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055857919","display_name":"Chenhao Ma","orcid":"https://orcid.org/0000-0002-3243-8512","observed_orcids":["https://orcid.org/0000-0002-3243-8512"]},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenhao Ma","raw_affiliation_strings":["Chinese University of Hong Kong, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-3243-8512","affiliations":[{"raw_affiliation_string":"Chinese University of Hong Kong, Shenzhen, China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5121828039","display_name":"Xuequn Shang","orcid":"https://orcid.org/0000-0002-7249-8210","observed_orcids":["https://orcid.org/0000-0002-7249-8210"]},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuequn Shang","raw_affiliation_strings":["Northwestern Polytechnical University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0002-7249-8210","affiliations":[{"raw_affiliation_string":"Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":6.8347,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.95842274,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"38","issue":"5","first_page":"2793","last_page":"2806"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.6021000146865845,"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":0.6021000146865845,"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":0.38179999589920044,"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":0.005400000140070915,"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/anomaly-detection","display_name":"anomaly detection","score":0.7749999761581421},{"id":"https://openalex.org/keywords/explainable-ai","display_name":"explainable AI","score":0.6850000023841858},{"id":"https://openalex.org/keywords/dynamic-heterogeneous-graphs","display_name":"dynamic heterogeneous graphs","score":0.9879999756813049},{"id":"https://openalex.org/keywords/temporal-graph-learning","display_name":"temporal graph learning","score":0.5889999866485596},{"id":"https://openalex.org/keywords/prototype-alignment","display_name":"prototype alignment","score":0.7760000228881836},{"id":"https://openalex.org/keywords/interpretability","display_name":"interpretability","score":0.6930000185966492},{"id":"https://openalex.org/keywords/abnormal-behavior-detection","display_name":"abnormal behavior detection","score":0.8579999804496765},{"id":"https://openalex.org/keywords/social-networks","display_name":"social networks","score":0.6449999809265137},{"id":"https://openalex.org/keywords/financial-transactions","display_name":"financial transactions","score":0.6759999990463257},{"id":"https://openalex.org/keywords/cybersecurity","display_name":"cybersecurity","score":0.6259999871253967}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9593999981880188},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8324999809265137},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7695000171661377},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7092999815940857},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5582000017166138},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.5471000075340271},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47920000553131104},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.40630000829696655},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39899998903274536},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3650999963283539},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3483999967575073},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3264000117778778},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.3061000108718872},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.3050000071525574},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29120001196861267},{"id":"https://openalex.org/C158207573","wikidata":"https://www.wikidata.org/wiki/Q5747224","display_name":"Heterogeneous network","level":4,"score":0.2806999981403351},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.26170000433921814},{"id":"https://openalex.org/C159246509","wikidata":"https://www.wikidata.org/wiki/Q5428725","display_name":"Factor graph","level":3,"score":0.26019999384880066}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2026.3665892","doi":"https://doi.org/10.1109/tkde.2026.3665892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2026.3665892","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","ccf-a","cwts-core","dongbi-a","fnege-3","jufo-3","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G1392884172","display_name":null,"funder_award_id":"62302421","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1689133894","display_name":null,"funder_award_id":"62302397","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3825787491","display_name":null,"funder_award_id":"62433016","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6862826674","display_name":null,"funder_award_id":"2025M774364","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"}],"funders":[{"id":"https://openalex.org/F3953416623","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W2079460424","https://openalex.org/W2089554624","https://openalex.org/W2128728535","https://openalex.org/W2284900416","https://openalex.org/W2295128594","https://openalex.org/W2604314403","https://openalex.org/W2669485504","https://openalex.org/W2808771744","https://openalex.org/W2907991115","https://openalex.org/W2911286998","https://openalex.org/W2944250323","https://openalex.org/W2966841471","https://openalex.org/W2970398671","https://openalex.org/W2982200221","https://openalex.org/W2996910652","https://openalex.org/W3004507689","https://openalex.org/W3008150054","https://openalex.org/W3012871709","https://openalex.org/W3019320019","https://openalex.org/W3045255111","https://openalex.org/W3080203535","https://openalex.org/W3093649180","https://openalex.org/W3096561660","https://openalex.org/W3112278336","https://openalex.org/W3126367810","https://openalex.org/W3156449551","https://openalex.org/W3156926010","https://openalex.org/W3156989090","https://openalex.org/W3168729505","https://openalex.org/W3174048174","https://openalex.org/W3175971420","https://openalex.org/W3177385106","https://openalex.org/W3190794503","https://openalex.org/W3191802839","https://openalex.org/W3194651497","https://openalex.org/W3208881055","https://openalex.org/W4221136088","https://openalex.org/W4226139613","https://openalex.org/W4290877309","https://openalex.org/W4290927873","https://openalex.org/W4323343820","https://openalex.org/W4362653719","https://openalex.org/W4368232640","https://openalex.org/W4382202833","https://openalex.org/W4382202909","https://openalex.org/W4382239148","https://openalex.org/W4382239841","https://openalex.org/W4385562644","https://openalex.org/W4385562708","https://openalex.org/W4385565420","https://openalex.org/W4385768068","https://openalex.org/W4387848560","https://openalex.org/W4387849006","https://openalex.org/W4388107294","https://openalex.org/W4389948071","https://openalex.org/W4391004041","https://openalex.org/W4392011725","https://openalex.org/W4399121544","https://openalex.org/W4401033222","https://openalex.org/W4401070657","https://openalex.org/W4401642181","https://openalex.org/W4403555783","https://openalex.org/W4410637101","https://openalex.org/W4413349568","https://openalex.org/W4415800637","https://openalex.org/W7118009992","https://openalex.org/W7133195610","https://openalex.org/W7133236456"],"related_works":["https://openalex.org/W4410637101","https://openalex.org/W4414638653","https://openalex.org/W2522429841","https://openalex.org/W4411996073","https://openalex.org/W4409363174","https://openalex.org/W4411248054","https://openalex.org/W7166471325","https://openalex.org/W7197012048","https://openalex.org/W3037008030","https://openalex.org/W4388107294"],"abstract_inverted_index":{"Abnormal":[0],"behavior":[1,49],"detection":[2,51,83],"is":[3,131,155],"crucial":[4],"in":[5,149],"many":[6],"fields,":[7],"such":[8],"as":[9],"social":[10],"networks,":[11],"financial":[12],"transactions,":[13],"and":[14,31,67,77],"cyber":[15],"security.":[16],"However,":[17],"it":[18,141],"poses":[19],"significant":[20],"challenges":[21],"due":[22],"to":[23,62,73,121],"the":[24,32],"intricate":[25],"structural":[26,60],"evolution":[27,61],"of":[28,89,97],"heterogeneous":[29,54,151],"graphs":[30],"need":[33],"for":[34,52],"explainable":[35],"models.":[36],"To":[37],"address":[38],"these":[39],"issues,":[40],"we":[41],"propose":[42],"a":[43,69,143],"novel":[44],"method":[45],"called":[46],"Explainable":[47],"anomalous":[48,110],"(edge)":[50],"dynamic":[53,150],"Graphs":[55],"(ExpGraph).":[56],"ExpGraph":[57,123,130],"captures":[58],"relation-aware":[59],"model":[63],"temporal":[64],"behavioral":[65],"patterns":[66],"introduces":[68],"prototype":[70,80],"alignment":[71,81],"mechanism":[72],"improve":[74],"both":[75],"performance":[76],"interpretability.":[78],"Specifically,":[79],"enhances":[82],"by":[84,103],"en":[85],"couraging":[86],"discriminative":[87],"representations":[88],"normal":[90,115],"behaviors,":[91],"which":[92],"facilitates":[93],"more":[94,133],"accurate":[95],"identification":[96],"anomalies.":[98],"It":[99,127],"also":[100],"improves":[101],"interpretability":[102],"enabling":[104],"intuitive":[105],"explanations":[106],"through":[107],"measuring":[108],"how":[109],"behaviors":[111,148],"differ":[112],"from":[113],"learned":[114],"prototypes.":[116],"We":[117],"conduct":[118],"extensive":[119],"experiments":[120],"evaluate":[122],"against":[124],"advanced":[125],"competitors.":[126],"demonstrates":[128],"that":[129],"16.2%":[132],"effective":[134],"than":[135],"other":[136],"methods":[137],"on":[138],"average.":[139],"Moreover,":[140],"offers":[142],"deeper":[144],"insight":[145],"into":[146],"abnormal":[147],"graphs.":[152],"Our":[153],"code":[154],"available":[156],"at":[157],"https://github.com/anonymous-123a/ExpGraph.":[158]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-02-18T00:00:00"}
