{"id":"https://openalex.org/W4391054868","doi":"https://doi.org/10.14778/3632093.3632110","title":"An Experimental Evaluation of Anomaly Detection in Time Series","display_name":"An Experimental Evaluation of Anomaly Detection in Time Series","publication_year":2023,"publication_date":"2023-11-01","ids":{"openalex":"https://openalex.org/W4391054868","doi":"https://doi.org/10.14778/3632093.3632110"},"language":"en","primary_location":{"id":"doi:10.14778/3632093.3632110","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3632093.3632110","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the VLDB Endowment","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/A5025469862","display_name":"Aoqian Zhang","orcid":"https://orcid.org/0000-0003-4059-6913"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Aoqian Zhang","raw_affiliation_strings":["Beijing Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024017792","display_name":"Shuqing Deng","orcid":"https://orcid.org/0000-0002-1429-1326"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuqing Deng","raw_affiliation_strings":["Beijing Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113100562","display_name":"Dongping Cui","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongping Cui","raw_affiliation_strings":["Beijing Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014346487","display_name":"Ye Yuan","orcid":"https://orcid.org/0000-0002-0247-9866"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ye Yuan","raw_affiliation_strings":["Beijing Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054991337","display_name":"Guoren Wang","orcid":"https://orcid.org/0000-0002-0181-8379"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoren Wang","raw_affiliation_strings":["Beijing Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5025469862"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":2.2728,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.90738316,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"17","issue":"3","first_page":"483","last_page":"496"},"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":0.9994999766349792,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9962999820709229,"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":0.836000919342041},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6910613775253296},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6243122816085815},{"id":"https://openalex.org/keywords/subsequence","display_name":"Subsequence","score":0.6213771104812622},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5553469061851501},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5542084574699402},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5323719382286072},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5144662857055664},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4778316020965576},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.44757795333862305},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35423561930656433},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3388977646827698},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1478748917579651},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10405173897743225},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07627204060554504}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.836000919342041},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6910613775253296},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6243122816085815},{"id":"https://openalex.org/C137877099","wikidata":"https://www.wikidata.org/wiki/Q1332977","display_name":"Subsequence","level":3,"score":0.6213771104812622},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5553469061851501},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5542084574699402},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5323719382286072},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5144662857055664},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4778316020965576},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.44757795333862305},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35423561930656433},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3388977646827698},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1478748917579651},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10405173897743225},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07627204060554504},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.14778/3632093.3632110","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3632093.3632110","pdf_url":null,"source":{"id":"https://openalex.org/S4210226185","display_name":"Proceedings of the VLDB Endowment","issn_l":"2150-8097","issn":["2150-8097"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the VLDB Endowment","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.5899999737739563,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W639218804","https://openalex.org/W1970814655","https://openalex.org/W1989650021","https://openalex.org/W2011436309","https://openalex.org/W2021651899","https://openalex.org/W2026493302","https://openalex.org/W2041376115","https://openalex.org/W2049058890","https://openalex.org/W2104410989","https://openalex.org/W2105686649","https://openalex.org/W2111848762","https://openalex.org/W2113049098","https://openalex.org/W2191950414","https://openalex.org/W2337344967","https://openalex.org/W2548218624","https://openalex.org/W2667207928","https://openalex.org/W2743617586","https://openalex.org/W2785362611","https://openalex.org/W2786827964","https://openalex.org/W2898322183","https://openalex.org/W2950361482","https://openalex.org/W2964336507","https://openalex.org/W2970207504","https://openalex.org/W2997546679","https://openalex.org/W3004207920","https://openalex.org/W3008690657","https://openalex.org/W3028608787","https://openalex.org/W3030237437","https://openalex.org/W3080585419","https://openalex.org/W3081470858","https://openalex.org/W3086558596","https://openalex.org/W3106543020","https://openalex.org/W3135644052","https://openalex.org/W3138821899","https://openalex.org/W3169450514","https://openalex.org/W3170981104","https://openalex.org/W3176476506","https://openalex.org/W3198800015","https://openalex.org/W3200258828","https://openalex.org/W4225539031","https://openalex.org/W4233200032","https://openalex.org/W4241727697","https://openalex.org/W4283318673","https://openalex.org/W4283324222","https://openalex.org/W4288057688","https://openalex.org/W4312750676","https://openalex.org/W4312757401","https://openalex.org/W4316020342","https://openalex.org/W4376453806"],"related_works":["https://openalex.org/W3031281630","https://openalex.org/W2806741695","https://openalex.org/W3210364259","https://openalex.org/W4290647774","https://openalex.org/W3197626606","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W4300558037"],"abstract_inverted_index":{"Anomaly":[0],"detection":[1,79],"in":[2,11,47,120,132,146,171,184],"time":[3,133,185],"series":[4,134,186],"data":[5,87,156],"has":[6],"been":[7,20],"studied":[8],"for":[9,22,60,67,129,181],"decades":[10],"both":[12],"statistics":[13],"and":[14,32,52,91,94,102,111,123,143,151,163,187],"computer":[15],"science.":[16],"Various":[17],"algorithms":[18,108,142],"have":[19],"proposed":[21],"different":[23,172],"scenarios,":[24],"such":[25],"as":[26],"fraud":[27],"detection,":[28],"environmental":[29],"monitoring,":[30],"manufacturing,":[31],"healthcare.":[33],"However,":[34],"there":[35],"is":[36],"a":[37,75,115,124,178],"lack":[38],"of":[39,42,77,105,140,148,159],"comparative":[40],"evaluation":[41],"these":[43,141],"state-of-the-art":[44,107],"approaches,":[45],"especially":[46],"the":[48,54,83,138],"same":[49,55],"test":[50,144,168],"environment":[51],"with":[53,114],"benchmark,":[56],"making":[57],"it":[58],"difficult":[59],"users":[61],"to":[62,153],"select":[63],"an":[64],"appropriate":[65],"method":[66],"real-world":[68],"applications.":[69],"In":[70],"this":[71],"paper,":[72],"we":[73,176],"present":[74],"taxonomy":[76],"anomaly":[78,92,154,161],"methods":[80],"based":[81],"on":[82,109],"main":[84],"features,":[85],"i.e.,":[86],"dimension,":[88],"processing":[89],"technique,":[90],"type":[93],"six":[95],"inner":[96],"classes.":[97],"We":[98,136,166],"perform":[99],"systematic":[100],"intra-":[101],"inter-class":[103],"comparisons":[104],"seventeen":[106],"real":[110],"synthetic":[112],"datasets":[113],"point":[116],"metric":[117,126],"commonly":[118],"used":[119],"classification":[121],"problems":[122],"range":[125],"specifically":[127],"designed":[128],"subsequence":[130],"anomalies":[131,183],"data.":[135],"analyze":[137],"properties":[139],"them":[145],"terms":[147],"effectiveness,":[149],"efficiency,":[150],"robustness":[152],"rates,":[155],"sizes,":[157],"number":[158],"dimensions,":[160],"patterns,":[162],"threshold":[164],"settings.":[165],"also":[167],"their":[169],"performance":[170],"use":[173],"cases.":[174],"Finally,":[175],"provide":[177],"practical":[179],"guide":[180],"detecting":[182],"discussions.":[188]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
