{"id":"https://openalex.org/W4229021642","doi":"https://doi.org/10.1145/3477314.3507024","title":"\"Do you know existing accuracy metrics overrate time-series anomaly detections?\"","display_name":"\"Do you know existing accuracy metrics overrate time-series anomaly detections?\"","publication_year":2022,"publication_date":"2022-04-25","ids":{"openalex":"https://openalex.org/W4229021642","doi":"https://doi.org/10.1145/3477314.3507024"},"language":"en","primary_location":{"id":"doi:10.1145/3477314.3507024","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3477314.3507024","pdf_url":null,"source":{"id":"https://openalex.org/S4363608665","display_name":"Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing","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 37th ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-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/A5014643514","display_name":"Wonseok Hwang","orcid":null},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Won-Seok Hwang","raw_affiliation_strings":["The Affiliated Institute of ETRI, Daejeon, South Korea"],"affiliations":[{"raw_affiliation_string":"The Affiliated Institute of ETRI, Daejeon, South Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112052807","display_name":"Jeong-Han Yun","orcid":null},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jeong-Han Yun","raw_affiliation_strings":["The Affiliated Institute of ETRI, Daejeon, South Korea"],"affiliations":[{"raw_affiliation_string":"The Affiliated Institute of ETRI, Daejeon, South Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114859940","display_name":"Jonguk Kim","orcid":"https://orcid.org/0000-0001-5277-3273"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jonguk Kim","raw_affiliation_strings":["The Affiliated Institute of ETRI, Daejeon, South Korea"],"affiliations":[{"raw_affiliation_string":"The Affiliated Institute of ETRI, Daejeon, South Korea","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110772577","display_name":"Byung Gil Min","orcid":null},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Byung Gil Min","raw_affiliation_strings":["The Affiliated Institute of ETRI, Daejeon, South Korea"],"affiliations":[{"raw_affiliation_string":"The Affiliated Institute of ETRI, Daejeon, South Korea","institution_ids":["https://openalex.org/I142401562"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5014643514"],"corresponding_institution_ids":["https://openalex.org/I142401562"],"apc_list":null,"apc_paid":null,"fwci":1.7641,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.86619263,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"403","last_page":"412"},"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9990000128746033,"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"}},{"id":"https://openalex.org/T10917","display_name":"Smart Grid Security and Resilience","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.8400239944458008},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.7953254580497742},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.7874338626861572},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.7155194878578186},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.643153965473175},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6385108828544617},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5686951279640198},{"id":"https://openalex.org/keywords/a-weighting","display_name":"A-weighting","score":0.44575947523117065},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4326592981815338},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3932330310344696},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3784200847148895},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06761953234672546}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8400239944458008},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.7953254580497742},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.7874338626861572},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.7155194878578186},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.643153965473175},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6385108828544617},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5686951279640198},{"id":"https://openalex.org/C70136482","wikidata":"https://www.wikidata.org/wiki/Q13583781","display_name":"A-weighting","level":3,"score":0.44575947523117065},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4326592981815338},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3932330310344696},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3784200847148895},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06761953234672546},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","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},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3477314.3507024","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3477314.3507024","pdf_url":null,"source":{"id":"https://openalex.org/S4363608665","display_name":"Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing","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 37th ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8500000238418579,"display_name":"Clean water and sanitation","id":"https://metadata.un.org/sdg/6"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1485718738","https://openalex.org/W1682770403","https://openalex.org/W2102150307","https://openalex.org/W2132870739","https://openalex.org/W2140190241","https://openalex.org/W2157331557","https://openalex.org/W2767248183","https://openalex.org/W2768947629","https://openalex.org/W2785362611","https://openalex.org/W2950361482","https://openalex.org/W2984333088","https://openalex.org/W3013803552","https://openalex.org/W3031577140","https://openalex.org/W3081497074","https://openalex.org/W3098957257","https://openalex.org/W3099971460","https://openalex.org/W4256257383"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W2092002118","https://openalex.org/W1880952682","https://openalex.org/W3210364259","https://openalex.org/W4290647774","https://openalex.org/W1963516324","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W2014269659","https://openalex.org/W2912112202"],"abstract_inverted_index":{"An":[0],"anomaly":[1,30,104,111,126,136,289],"coincides":[2],"with":[3,90,179],"a":[4,11,42,46,81,84,106,128,145,165,174,188,288],"time":[5],"range":[6,31,86,112,133],"in":[7,161,198,281,287],"time-series":[8],"data,":[9],"and":[10,71,187,195,200,239,263],"detection":[12,43,61,290],"method":[13,44,62],"usually":[14],"detects":[15],"part":[16,130],"of":[17,131,147,158,185,218],"this":[18,39],"range.":[19],"Existing":[20],"works":[21],"assume":[22],"that":[23,87,243],"an":[24,95,103,109,115,125],"expert":[25,40,51,75,171],"can":[26,52],"detect":[27,77,102],"the":[28,50,60,66,132,135,150,156,170,210,215,244],"whole":[29],"by":[32,59],"analyzing":[33],"its":[34,141],"detected":[35],"part.":[36],"Based":[37,229],"on":[38,230],"scenario,":[41],"achieves":[45],"higher":[47],"score":[48,163],"if":[49,80,105,134],"find":[53],"more":[54,172,248],"anomalies":[55,79,92,194],"through":[56,182],"predictions":[57,160,196,226],"given":[58,220],"as":[63,269,271],"clues.":[64],"However,":[65],"existing":[67,151,252],"metrics":[68,152,236,246,253,277],"overrate":[69],"imprecise":[70,96,199],"insufficient":[72,110,116,201],"cases.":[73],"The":[74,191],"cannot":[76],"any":[78,91],"prediction":[82,107,168],"indicates":[83,108],"wrong":[85],"is":[88,121],"unrelated":[89],"(i.e.,":[93,113,237,292],"called":[94,114],"case).":[97,117],"Moreover,":[98,149],"they":[99,284],"fail":[100],"to":[101,123,221,251],"For":[118],"instance,":[119],"it":[120],"difficult":[122],"understand":[124],"using":[127,256],"small":[129],"has":[137],"steadily":[138],"changed":[139],"from":[140,205],"original":[142],"pattern":[143],"over":[144],"period":[146],"time.":[148],"do":[153],"not":[154],"consider":[155,214],"length":[157],"incorrect":[159,167,225],"their":[162],"though":[164],"prolonged":[166],"incoveniences":[169],"than":[173],"shorter":[175],"one.":[176],"We":[177,241],"deal":[178],"these":[180,231],"problems":[181],"two":[183,257],"concepts":[184],"cross-referencing":[186,192],"weighting":[189,211],"scheme.":[190],"verifies":[193],"involved":[197],"cases,":[202],"preventing":[203],"them":[204],"getting":[206],"scores.":[207],"By":[208],"adopting":[209],"scheme,":[212],"we":[213,233],"weighted":[216],"sum":[217],"scores":[219],"predictions,":[222],"wherein":[223],"lengthy":[224],"are":[227,247,285],"penalized.":[228],"concepts,":[232],"propose":[234],"novel":[235],"eTaV":[238],"eTaff).":[240],"verify":[242],"proposed":[245],"reasonable":[249],"compared":[250],"via":[254],"evaluations":[255],"real-world":[258],"datasets,":[259],"Secure":[260],"Water":[261],"Treatment":[262],"Hardware-in-the-Loop-based":[264],"Augmented":[265],"Industrial":[266],"control":[267],"system":[268],"well":[270],"some":[272],"hypothetical":[273],"datasets.":[274],"Furthermore,":[275],"our":[276],"have":[278],"been":[279],"verified":[280],"practice":[282],"because":[283],"employed":[286],"competition":[291],"HAICon'211).":[293]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2026-02-28T09:26:25.869077","created_date":"2025-10-10T00:00:00"}