{"id":"https://openalex.org/W4285603061","doi":"https://doi.org/10.24963/ijcai.2022/801","title":"Experimental Comparison and Survey of Twelve Time Series Anomaly Detection Algorithms (Extended Abstract)","display_name":"Experimental Comparison and Survey of Twelve Time Series Anomaly Detection Algorithms (Extended Abstract)","publication_year":2022,"publication_date":"2022-07-01","ids":{"openalex":"https://openalex.org/W4285603061","doi":"https://doi.org/10.24963/ijcai.2022/801"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2022/801","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/801","pdf_url":"https://www.ijcai.org/proceedings/2022/0801.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.ijcai.org/proceedings/2022/0801.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086018905","display_name":"Cynthia Freeman","orcid":null},"institutions":[{"id":"https://openalex.org/I4210138417","display_name":"Verint Systems (United States)","ror":"https://ror.org/03fqhrc68","country_code":"US","type":"company","lineage":["https://openalex.org/I4210138417"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cynthia Freeman","raw_affiliation_strings":["Verint Systems Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Verint Systems Inc","institution_ids":["https://openalex.org/I4210138417"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021843768","display_name":"Jonathan Merriman","orcid":null},"institutions":[{"id":"https://openalex.org/I4210138417","display_name":"Verint Systems (United States)","ror":"https://ror.org/03fqhrc68","country_code":"US","type":"company","lineage":["https://openalex.org/I4210138417"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jonathan Merriman","raw_affiliation_strings":["Verint Systems Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Verint Systems Inc","institution_ids":["https://openalex.org/I4210138417"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046481287","display_name":"Ian Beaver","orcid":"https://orcid.org/0000-0003-0865-1214"},"institutions":[{"id":"https://openalex.org/I4210138417","display_name":"Verint Systems (United States)","ror":"https://ror.org/03fqhrc68","country_code":"US","type":"company","lineage":["https://openalex.org/I4210138417"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ian Beaver","raw_affiliation_strings":["Verint Systems Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Verint Systems Inc","institution_ids":["https://openalex.org/I4210138417"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025138797","display_name":"Abdullah Mueen","orcid":"https://orcid.org/0000-0002-4839-1624"},"institutions":[{"id":"https://openalex.org/I169521973","display_name":"University of New Mexico","ror":"https://ror.org/05fs6jp91","country_code":"US","type":"education","lineage":["https://openalex.org/I169521973"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abdullah Mueen","raw_affiliation_strings":["University of New Mexico, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of New Mexico, USA","institution_ids":["https://openalex.org/I169521973"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1038,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.2658362,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"5737","last_page":"5741"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9994999766349792,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9979000091552734,"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":0.9174924492835999},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7845728397369385},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.7812355756759644},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6955670714378357},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6186866164207458},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5770071148872375},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5591033697128296},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34225353598594666},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3380882740020752},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.07049494981765747}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.9174924492835999},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7845728397369385},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.7812355756759644},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6955670714378357},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6186866164207458},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5770071148872375},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5591033697128296},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34225353598594666},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3380882740020752},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.07049494981765747},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"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:10.24963/ijcai.2022/801","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/801","pdf_url":"https://www.ijcai.org/proceedings/2022/0801.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2022/801","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2022/801","pdf_url":"https://www.ijcai.org/proceedings/2022/0801.pdf","source":{"id":"https://openalex.org/S4363608755","display_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4285603061.pdf","grobid_xml":"https://content.openalex.org/works/W4285603061.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W87496662","https://openalex.org/W201138236","https://openalex.org/W1565746575","https://openalex.org/W2020865809","https://openalex.org/W2026493302","https://openalex.org/W2093606067","https://openalex.org/W2278984902","https://openalex.org/W2282861635","https://openalex.org/W2608459225","https://openalex.org/W2702877955","https://openalex.org/W2766183090","https://openalex.org/W2790057819","https://openalex.org/W2794778778","https://openalex.org/W3004207920","https://openalex.org/W3021858395","https://openalex.org/W3098957257","https://openalex.org/W3208688400","https://openalex.org/W3215189916","https://openalex.org/W4297789735"],"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/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4377864969","https://openalex.org/W2972971679"],"abstract_inverted_index":{"The":[0],"existence":[1],"of":[2,21,33,47,93,146,195,203],"an":[3,90,209],"anomaly":[4,22,66,95,115,148,191,204],"detection":[5,23,67,96,116,149,192,205],"method":[6,55,97],"that":[7],"is":[8,13,61,98],"optimal":[9,114],"for":[10,29,56,72],"all":[11],"domains":[12],"a":[14,19,30,36,41,140,199],"myth.":[15],"Thus,":[16],"there":[17],"exists":[18],"plethora":[20],"methods":[24,68,76,117,150,193],"which":[25],"increases":[26],"every":[27,94],"year":[28],"wide":[31],"variety":[32],"domains.":[34],"But":[35],"strength":[37],"can":[38,50,181],"also":[39],"be":[40],"weakness;":[42],"given":[43],"this":[44,104],"massive":[45],"library":[46,202],"methods,":[48,206],"how":[49],"one":[51],"select":[52],"the":[53,78,85,113,120,122,163,167,188],"best":[54],"their":[57],"application?":[58],"Current":[59],"literature":[60,86],"focused":[62],"on":[63,119,160],"creating":[64],"new":[65],"or":[69],"large":[70],"frameworks":[71],"experimenting":[73,196],"with":[74,198],"multiple":[75],"at":[77],"same":[79],"time.":[80],"However,":[81],"and":[82,134,144,171,184],"especially":[83,207],"as":[84,127],"continues":[87],"to":[88,110,156],"expand,":[89],"extensive":[91],"evaluation":[92,105],"simply":[99],"not":[100],"feasible.":[101],"To":[102],"reduce":[103],"burden,":[106],"we":[107],"present":[108],"guidelines":[109,158],"intelligently":[111],"choose":[112],"based":[118,159],"characteristics":[121,155],"time":[123,136,153,183],"series":[124,154],"displays":[125],"such":[126],"seasonality,":[128],"trend,":[129],"level":[130],"change":[131],"concept":[132],"drift,":[133],"missing":[135],"steps.":[137],"We":[138],"provide":[139],"comprehensive":[141],"experimental":[142],"validation":[143],"survey":[145],"twelve":[147],"over":[151],"different":[152],"form":[157],"several":[161],"metrics:":[162],"AUC":[164],"(Area":[165],"Under":[166],"Curve),":[168],"windowed":[169],"F-score,":[170],"Numenta":[172],"Anomaly":[173],"Benchmark":[174],"(NAB)":[175],"scoring":[176],"model.":[177],"Applying":[178],"our":[179],"methodologies":[180],"save":[182],"effort":[185],"by":[186],"surfacing":[187],"most":[189],"promising":[190],"instead":[194],"extensively":[197],"rapidly":[200],"expanding":[201],"in":[208],"online":[210],"setting.":[211]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}