{"id":"https://openalex.org/W4392172850","doi":"https://doi.org/10.1109/tim.2024.3369159","title":"Asymptotic Consistent Graph Structure Learning for Multivariate Time-Series Anomaly Detection","display_name":"Asymptotic Consistent Graph Structure Learning for Multivariate Time-Series Anomaly Detection","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4392172850","doi":"https://doi.org/10.1109/tim.2024.3369159"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2024.3369159","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2024.3369159","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Instrumentation and Measurement","raw_type":"journal-article"},"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/A5003815633","display_name":"Huaxin Pang","orcid":"https://orcid.org/0000-0003-4998-4576"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Huaxin Pang","raw_affiliation_strings":["School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006854141","display_name":"Shikui Wei","orcid":"https://orcid.org/0000-0003-3803-9763"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shikui Wei","raw_affiliation_strings":["School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024633033","display_name":"Youru Li","orcid":"https://orcid.org/0000-0002-9326-9863"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youru Li","raw_affiliation_strings":["School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057382261","display_name":"Ting Liu","orcid":"https://orcid.org/0000-0003-3458-6567"},"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":"Ting Liu","raw_affiliation_strings":["School of Computer Science, Northwestern Polytechnical University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108830770","display_name":"Huaqi Zhang","orcid":"https://orcid.org/0000-0003-2552-9640"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaqi Zhang","raw_affiliation_strings":["School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013250925","display_name":"Ying Qin","orcid":"https://orcid.org/0000-0003-4606-7174"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Qin","raw_affiliation_strings":["School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100362745","display_name":"Yao Zhao","orcid":"https://orcid.org/0000-0002-8581-9554"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Zhao","raw_affiliation_strings":["School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5003815633"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":4.6552,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.9515916,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"73","issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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":1.0,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9921000003814697,"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/anomaly-detection","display_name":"Anomaly detection","score":0.6631518602371216},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.6353965401649475},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5913983583450317},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5485967397689819},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5428497791290283},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4863151013851166},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4733850061893463},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.4656902551651001},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3891561031341553},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3014536499977112},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2264913022518158},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1683015525341034},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.12815845012664795}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6631518602371216},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6353965401649475},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5913983583450317},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5485967397689819},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5428497791290283},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4863151013851166},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4733850061893463},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.4656902551651001},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3891561031341553},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3014536499977112},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2264913022518158},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1683015525341034},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.12815845012664795},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2024.3369159","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2024.3369159","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3467075038","display_name":null,"funder_award_id":"52202486","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5655896502","display_name":null,"funder_award_id":"62120106009","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6272256563","display_name":null,"funder_award_id":"2021ZD0112100","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G7536822468","display_name":null,"funder_award_id":"U1936212","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8332994597","display_name":null,"funder_award_id":"62106201","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"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1548644355","https://openalex.org/W2049058890","https://openalex.org/W2407991977","https://openalex.org/W2786827964","https://openalex.org/W2891373952","https://openalex.org/W2911200746","https://openalex.org/W2950361482","https://openalex.org/W2962736999","https://openalex.org/W2963166639","https://openalex.org/W2964248614","https://openalex.org/W2995962413","https://openalex.org/W3014309328","https://openalex.org/W3039222472","https://openalex.org/W3081497074","https://openalex.org/W3085139254","https://openalex.org/W3106543020","https://openalex.org/W3116132308","https://openalex.org/W3128634608","https://openalex.org/W3169450514","https://openalex.org/W3170937175","https://openalex.org/W3184127157","https://openalex.org/W3190748826","https://openalex.org/W4206020427","https://openalex.org/W4283318673","https://openalex.org/W4285600291","https://openalex.org/W4292963524","https://openalex.org/W4309873459","https://openalex.org/W4312458394","https://openalex.org/W4312800552","https://openalex.org/W4319452118","https://openalex.org/W4362500694","https://openalex.org/W4385245566","https://openalex.org/W4386825474","https://openalex.org/W4401567681","https://openalex.org/W6720006811","https://openalex.org/W6720514713","https://openalex.org/W6726873649","https://openalex.org/W6738964360","https://openalex.org/W6745537798","https://openalex.org/W6748102297","https://openalex.org/W6754929296","https://openalex.org/W6771931584","https://openalex.org/W6802061597","https://openalex.org/W6810225340","https://openalex.org/W6846768106","https://openalex.org/W6849411243","https://openalex.org/W6854278629"],"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":{"Capturing":[0],"complex":[1,28],"inter-variable":[2,29,64,173],"relationships":[3,30,65],"is":[4,102,129,167],"crucial":[5],"for":[6,9,85,109],"anomaly":[7,42,89,152,198],"detection":[8,43],"multivariate":[10,86],"time":[11,68,87,138],"series":[12,88],"(MTS)":[13],"data.":[14],"In":[15],"recent":[16],"years,":[17],"graph":[18,126],"neural":[19],"networks":[20],"(GNNs)":[21],"have":[22],"been":[23],"introduced":[24],"to":[25,61,104,131,169],"explicitly":[26,170],"model":[27],"from":[31],"global":[32],"static":[33],"or":[34,59,180],"local":[35,178],"dynamic":[36],"views,":[37],"improving":[38],"the":[39,106,162,189],"performance":[40,149],"of":[41,159,193],"tasks":[44],"significantly.":[45],"However,":[46],"these":[47],"approaches":[48],"usually":[49],"ignore":[50],"exploring":[51],"distinct":[52],"interaction":[53,134],"patterns":[54],"within":[55],"short":[56],"context":[57],"windows":[58],"fail":[60],"capture":[62],"unbiased":[63,107],"over":[66,136,161,176],"longer":[67],"windows.":[69,139],"To":[70],"address":[71],"this":[72],"limitation,":[73],"we":[74],"propose":[75],"a":[76,92,99,116,156],"novel":[77],"Asymptotic":[78],"Consistent":[79],"Graph":[80,118],"Structure":[81],"Learning":[82],"(ACGSL)":[83],"framework":[84],"detection.":[90,199],"Specifically,":[91],"Sequence":[93],"Aggregation":[94],"Module":[95,120],"(SeAM)":[96],"together":[97],"with":[98],"denoising":[100],"filter":[101],"developed":[103],"learn":[105],"representation":[108],"each":[110],"temporal":[111],"variable":[112],"more":[113],"effectively.":[114],"Furthermore,":[115,165],"Feature-Accumulation":[117],"Construct":[119],"(FA-GCM)":[121],"enhanced":[122],"by":[123],"asymptotic":[124],"consistent":[125],"optimization":[127],"loss":[128],"proposed":[130,195],"construct":[132],"stable":[133,172],"graphs":[135,175],"adaptive":[137],"We":[140],"conduct":[141],"experiments":[142,184],"on":[143],"five":[144],"benchmarks":[145],"and":[146,185,191],"achieve":[147],"remarkable":[148],"enhancement":[150],"in":[151,197],"detection,":[153],"even":[154],"acquiring":[155],"maximum":[157],"gain":[158],"3.64%":[160],"second-best":[163],"baseline.":[164],"ACGSL":[166,196],"able":[168],"give":[171],"interacted":[174],"arbitrary":[177],"normal":[179],"anomalous":[181],"states.":[182],"Extensive":[183],"ablation":[186],"studies":[187],"demonstrate":[188],"effectiveness":[190],"robustness":[192],"our":[194]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":4}],"updated_date":"2026-03-17T09:09:15.849793","created_date":"2025-10-10T00:00:00"}