{"id":"https://openalex.org/W4283324222","doi":"https://doi.org/10.14778/3529337.3529354","title":"TSB-UAD","display_name":"TSB-UAD","publication_year":2022,"publication_date":"2022-04-01","ids":{"openalex":"https://openalex.org/W4283324222","doi":"https://doi.org/10.14778/3529337.3529354"},"language":"en","primary_location":{"id":"doi:10.14778/3529337.3529354","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3529337.3529354","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/A5091139670","display_name":"John Paparrizos","orcid":"https://orcid.org/0000-0002-7592-748X"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"John Paparrizos","raw_affiliation_strings":["University of Chicago"],"affiliations":[{"raw_affiliation_string":"University of Chicago","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066613721","display_name":"Yuhao Kang","orcid":"https://orcid.org/0000-0001-5393-434X"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuhao Kang","raw_affiliation_strings":["University of Chicago"],"affiliations":[{"raw_affiliation_string":"University of Chicago","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021057598","display_name":"Paul Boniol","orcid":"https://orcid.org/0000-0001-8516-0123"},"institutions":[{"id":"https://openalex.org/I204730241","display_name":"Universit\u00e9 Paris Cit\u00e9","ror":"https://ror.org/05f82e368","country_code":"FR","type":"education","lineage":["https://openalex.org/I204730241"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Paul Boniol","raw_affiliation_strings":["Universit\u00e9 de Paris"],"affiliations":[{"raw_affiliation_string":"Universit\u00e9 de Paris","institution_ids":["https://openalex.org/I204730241"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033579806","display_name":"Ruey S. Tsay","orcid":"https://orcid.org/0000-0002-4949-4035"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ruey S. Tsay","raw_affiliation_strings":["University of Chicago"],"affiliations":[{"raw_affiliation_string":"University of Chicago","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053726723","display_name":"Themis Palpanas","orcid":"https://orcid.org/0000-0002-8031-0265"},"institutions":[{"id":"https://openalex.org/I204730241","display_name":"Universit\u00e9 Paris Cit\u00e9","ror":"https://ror.org/05f82e368","country_code":"FR","type":"education","lineage":["https://openalex.org/I204730241"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Themis Palpanas","raw_affiliation_strings":["Universit\u00e9 de Paris &amp; IUF"],"affiliations":[{"raw_affiliation_string":"Universit\u00e9 de Paris &amp; IUF","institution_ids":["https://openalex.org/I204730241"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102019638","display_name":"Michael J. Franklin","orcid":"https://orcid.org/0000-0003-3332-8574"},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael J. Franklin","raw_affiliation_strings":["University of Chicago"],"affiliations":[{"raw_affiliation_string":"University of Chicago","institution_ids":["https://openalex.org/I40347166"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5091139670"],"corresponding_institution_ids":["https://openalex.org/I40347166"],"apc_list":null,"apc_paid":null,"fwci":13.5243,"has_fulltext":false,"cited_by_count":107,"citation_normalized_percentile":{"value":0.99069038,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"15","issue":"8","first_page":"1697","last_page":"1711"},"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":0.9997000098228455,"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/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9772999882698059,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/univariate","display_name":"Univariate","score":0.8056608438491821},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7805341482162476},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7316203117370605},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6922523975372314},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.6661072373390198},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.6156437993049622},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5779904127120972},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.5673105120658875},{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.464335560798645},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4139615595340729},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3027523159980774},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.20000261068344116},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09011566638946533}],"concepts":[{"id":"https://openalex.org/C199163554","wikidata":"https://www.wikidata.org/wiki/Q1681619","display_name":"Univariate","level":3,"score":0.8056608438491821},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7805341482162476},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7316203117370605},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6922523975372314},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.6661072373390198},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.6156437993049622},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5779904127120972},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.5673105120658875},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.464335560798645},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4139615595340729},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3027523159980774},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.20000261068344116},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09011566638946533},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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:10.14778/3529337.3529354","is_oa":false,"landing_page_url":"https://doi.org/10.14778/3529337.3529354","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":[{"score":0.4699999988079071,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":72,"referenced_works":["https://openalex.org/W4012559","https://openalex.org/W1527685850","https://openalex.org/W1541742946","https://openalex.org/W1543663519","https://openalex.org/W1586770701","https://openalex.org/W1985229168","https://openalex.org/W1989914875","https://openalex.org/W2000145235","https://openalex.org/W2013936649","https://openalex.org/W2026493302","https://openalex.org/W2037537012","https://openalex.org/W2048665112","https://openalex.org/W2052312648","https://openalex.org/W2053125529","https://openalex.org/W2095409369","https://openalex.org/W2103448012","https://openalex.org/W2106606334","https://openalex.org/W2108598243","https://openalex.org/W2110784166","https://openalex.org/W2125793385","https://openalex.org/W2126511896","https://openalex.org/W2127979711","https://openalex.org/W2128892560","https://openalex.org/W2144182447","https://openalex.org/W2148583977","https://openalex.org/W2152576712","https://openalex.org/W2156371275","https://openalex.org/W2182886880","https://openalex.org/W2296719434","https://openalex.org/W2535642622","https://openalex.org/W2548218624","https://openalex.org/W2560286635","https://openalex.org/W2620661538","https://openalex.org/W2622816133","https://openalex.org/W2702877955","https://openalex.org/W2734811990","https://openalex.org/W2808800115","https://openalex.org/W2888245863","https://openalex.org/W2906498146","https://openalex.org/W2911495555","https://openalex.org/W2950361482","https://openalex.org/W2962736999","https://openalex.org/W2963131120","https://openalex.org/W2966048283","https://openalex.org/W2970692043","https://openalex.org/W2970853883","https://openalex.org/W2972810968","https://openalex.org/W2994986075","https://openalex.org/W2997228838","https://openalex.org/W2997546679","https://openalex.org/W3010666283","https://openalex.org/W3029579534","https://openalex.org/W3031281630","https://openalex.org/W3081830030","https://openalex.org/W3083891030","https://openalex.org/W3086526924","https://openalex.org/W3135644052","https://openalex.org/W3146982637","https://openalex.org/W3155567600","https://openalex.org/W3175356203","https://openalex.org/W3176476506","https://openalex.org/W3179323212","https://openalex.org/W3188424408","https://openalex.org/W3197626606","https://openalex.org/W3198189630","https://openalex.org/W4212774754","https://openalex.org/W4241727697","https://openalex.org/W4252684946","https://openalex.org/W4254182148","https://openalex.org/W4256141317","https://openalex.org/W4393829392","https://openalex.org/W6940915336"],"related_works":["https://openalex.org/W39712736","https://openalex.org/W2806741695","https://openalex.org/W3210364259","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W2143820878","https://openalex.org/W2912112202","https://openalex.org/W2667207928","https://openalex.org/W3175321409"],"abstract_inverted_index":{"The":[0],"detection":[1,23,113,214,242],"of":[2,46,69,109,130,151,238],"anomalies":[3,123],"in":[4,58,64,92,100,188],"time":[5,119,144,157,170,190],"series":[6,120,145,158,171,191],"has":[7],"gained":[8],"ample":[9],"academic":[10],"and":[11,87,134,146,220,230],"industrial":[12],"attention.":[13],"However,":[14],"no":[15],"comprehensive":[16],"benchmark":[17,104],"exists":[18],"to":[19,28,37,83,105,234],"evaluate":[20,200],"time-series":[21,111,166,240],"anomaly":[22,112,131,196,213,241],"methods.":[24,114,215,243],"It":[25],"is":[26,207],"common":[27],"use":[29],"(i)":[30],"proprietary":[31],"or":[32,41],"synthetic":[33],"data,":[34],"often":[35,52],"biased":[36],"support":[38],"particular":[39],"claims;":[40],"(ii)":[42],"a":[43,102,160,208,227,236],"limited":[44],"collection":[45],"publicly":[47],"available":[48,222],"datasets.":[49,152],"Consequently,":[50],"we":[51,76,147,154,177,183,199],"observe":[53],"methods":[54,203],"performing":[55],"exceptionally":[56],"well":[57],"one":[59,80],"dataset":[60],"but":[61],"surprisingly":[62],"poorly":[63],"another,":[65],"creating":[66],"an":[67],"illusion":[68],"progress.":[70],"To":[71],"address":[72],"the":[73,93,107],"issues":[74],"above,":[75],"thoroughly":[77],"studied":[78],"over":[79],"hundred":[81],"papers":[82],"identify,":[84],"collect,":[85],"process,":[86],"systematically":[88],"format":[89],"datasets":[90,141,168],"proposed":[91,140],"past":[94],"decades.":[95],"We":[96,216],"summarize":[97],"our":[98,218],"effort":[99],"TSB-UAD,":[101],"new":[103,185],"ease":[106],"evaluation":[108],"univariate":[110,239],"Overall,":[115],"TSB-UAD":[116,136,206,225],"contains":[117],"13766":[118],"with":[121,127,172,181,192],"labeled":[122,173],"spanning":[124],"different":[125],"domains":[126],"high":[128],"variability":[129],"types,":[132],"ratios,":[133],"sizes.":[135],"includes":[137],"18":[138],"previously":[139],"containing":[142],"1980":[143],"contribute":[148],"two":[149],"collections":[150],"Specifically,":[153],"generate":[155],"958":[156],"using":[159],"principled":[161],"methodology":[162],"for":[163,195,211],"transforming":[164],"126":[165],"classification":[167],"into":[169],"anomalies.":[174],"In":[175],"addition,":[176],"present":[178],"data":[179,219],"transformations":[180],"which":[182],"introduce":[184],"anomalies,":[186],"resulting":[187],"10828":[189],"varying":[193],"complexity":[194],"detection.":[197],"Finally,":[198],"12":[201],"representative":[202],"demonstrating":[204],"that":[205],"robust":[209],"resource":[210,233],"assessing":[212],"make":[217],"code":[221],"at":[223],"www.timeseries.org/TSB-UAD.":[224],"provides":[226],"valuable,":[228],"reproducible,":[229],"frequently":[231],"updated":[232],"establish":[235],"leaderboard":[237]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":35},{"year":2024,"cited_by_count":31},{"year":2023,"cited_by_count":24},{"year":2022,"cited_by_count":8}],"updated_date":"2026-03-22T08:09:32.410652","created_date":"2022-06-24T00:00:00"}
