{"id":"https://openalex.org/W2833324965","doi":"https://doi.org/10.1109/mdm.2018.00029","title":"Outlier Detection for Multidimensional Time Series Using Deep Neural Networks","display_name":"Outlier Detection for Multidimensional Time Series Using Deep Neural Networks","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2833324965","doi":"https://doi.org/10.1109/mdm.2018.00029","mag":"2833324965"},"language":"en","primary_location":{"id":"doi:10.1109/mdm.2018.00029","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mdm.2018.00029","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 19th IEEE International Conference on Mobile Data Management (MDM)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5016799625","display_name":"Tung Kieu","orcid":"https://orcid.org/0000-0002-7696-1444"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Tung Kieu","raw_affiliation_strings":["Department of Computer Science, Aalborg University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Aalborg University","institution_ids":["https://openalex.org/I891191580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072309548","display_name":"Bin Yang","orcid":"https://orcid.org/0000-0002-1658-1079"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Bin Yang","raw_affiliation_strings":["Department of Computer Science, Aalborg University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Aalborg University","institution_ids":["https://openalex.org/I891191580"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029380368","display_name":"Christian S. Jensen","orcid":"https://orcid.org/0000-0002-9697-7670"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Christian S. Jensen","raw_affiliation_strings":["Department of Computer Science, Aalborg University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Aalborg University","institution_ids":["https://openalex.org/I891191580"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I891191580"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":191,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"125","last_page":"134"},"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/T14319","display_name":"Currency Recognition and Detection","score":0.9793000221252441,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.7723652124404907},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.771495521068573},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.7503005266189575},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7246477007865906},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.6991438865661621},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5780885815620422},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.5502427816390991},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5211220383644104},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49898838996887207},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4792742431163788},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.46090683341026306},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.43769371509552},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41800999641418457},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41139698028564453},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.39519163966178894}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7723652124404907},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.771495521068573},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7503005266189575},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7246477007865906},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.6991438865661621},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5780885815620422},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.5502427816390991},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5211220383644104},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49898838996887207},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4792742431163788},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.46090683341026306},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.43769371509552},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41800999641418457},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41139698028564453},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39519163966178894},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/mdm.2018.00029","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mdm.2018.00029","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 19th IEEE International Conference on Mobile Data Management (MDM)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:publications/118f02e4-1a1d-46d0-875d-3b1b0c12f025","is_oa":false,"landing_page_url":"http://www.scopus.com/inward/record.url?scp=85050812217&partnerID=8YFLogxK","pdf_url":null,"source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Kieu , T , Yang , B &amp; Jensen , C S 2018 , Outlier Detection for Multidimensional Time Series using Deep Neural Networks . in Proceedings of the 19th IEEE International Conference on Mobile Data Management, MDM 2018 . vol. 2018-June , IEEE , IEEE International Conference on Mobile Data Management (MDM) , pp. 125-134 , 19th IEEE International Conference on Mobile Data Management, MDM 2018 , Aalborg , Denmark , 25/06/2018 . https://doi.org/10.1109/MDM.2018.00029","raw_type":"contributionToPeriodical"},{"id":"pmh:oai:pure.atira.dk:publications/118f02e4-1a1d-46d0-875d-3b1b0c12f025","is_oa":false,"landing_page_url":"https://vbn.aau.dk/da/publications/118f02e4-1a1d-46d0-875d-3b1b0c12f025","pdf_url":null,"source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Kieu, T, Yang, B & Jensen, C S 2018, Outlier Detection for Multidimensional Time Series using Deep Neural Networks. in Proceedings of the 19th IEEE International Conference on Mobile Data Management, MDM 2018. vol. 2018-June, IEEE (Institute of Electrical and Electronics Engineers), IEEE International Conference on Mobile Data Management (MDM), pp. 125-134, 19th IEEE International Conference on Mobile Data Management, MDM 2018, Aalborg, Denmark, 25/06/2018. https://doi.org/10.1109/MDM.2018.00029","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320324292","display_name":"Det Obelske Familiefond","ror":"https://ror.org/032wd7d36"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W1489560600","https://openalex.org/W1522301498","https://openalex.org/W1523493493","https://openalex.org/W1936915774","https://openalex.org/W1979877030","https://openalex.org/W1998823014","https://openalex.org/W2002380285","https://openalex.org/W2002521620","https://openalex.org/W2008003976","https://openalex.org/W2010567219","https://openalex.org/W2026493302","https://openalex.org/W2036216970","https://openalex.org/W2049344225","https://openalex.org/W2064675550","https://openalex.org/W2069069662","https://openalex.org/W2097117768","https://openalex.org/W2100495367","https://openalex.org/W2101234009","https://openalex.org/W2105510466","https://openalex.org/W2120432001","https://openalex.org/W2124484773","https://openalex.org/W2127979711","https://openalex.org/W2129281431","https://openalex.org/W2131904035","https://openalex.org/W2144182447","https://openalex.org/W2151881411","https://openalex.org/W2158641899","https://openalex.org/W2163605009","https://openalex.org/W2191950414","https://openalex.org/W2204904589","https://openalex.org/W2326729945","https://openalex.org/W2333935798","https://openalex.org/W2384495648","https://openalex.org/W2464785945","https://openalex.org/W2474046725","https://openalex.org/W2525908418","https://openalex.org/W2566615221","https://openalex.org/W2567451611","https://openalex.org/W2573698050","https://openalex.org/W2578339457","https://openalex.org/W2605737181","https://openalex.org/W2618530766","https://openalex.org/W2622370560","https://openalex.org/W2667207928","https://openalex.org/W2768361919","https://openalex.org/W2770729327","https://openalex.org/W2785409760","https://openalex.org/W2795142517","https://openalex.org/W2795273206","https://openalex.org/W2964121744","https://openalex.org/W2997591727","https://openalex.org/W4253461361","https://openalex.org/W4254182148","https://openalex.org/W4256669726","https://openalex.org/W4297814361","https://openalex.org/W6629091462","https://openalex.org/W6631190155","https://openalex.org/W6679539681","https://openalex.org/W6710709672","https://openalex.org/W6719736774","https://openalex.org/W6720514713","https://openalex.org/W6749489344","https://openalex.org/W6750406613"],"related_works":["https://openalex.org/W3186512740","https://openalex.org/W2499612753","https://openalex.org/W4310873165","https://openalex.org/W4363671829","https://openalex.org/W2355395139","https://openalex.org/W2780476542","https://openalex.org/W3111802945","https://openalex.org/W4285596704","https://openalex.org/W2946096271","https://openalex.org/W1995622179"],"abstract_inverted_index":{"Due":[0],"to":[1,86,100,111,194],"the":[2,11,31,88,102,118,123,130,147,152,189,192,197,217,221],"continued":[3],"digitization":[4],"of":[5,13,22,33,46,91,122,146,161,185,199,220],"industrial":[6],"and":[7,49,72,165,173],"societal":[8],"processes,":[9],"including":[10],"deployment":[12],"networked":[14],"sensors,":[15],"we":[16,77,96,181],"are":[17],"witnessing":[18],"a":[19,43,53,80,114,128],"rapid":[20],"proliferation":[21],"time-ordered":[23],"observations,":[24],"known":[25],"as":[26,42,159],"time":[27,44,59,93,104,125,132,149,154,209],"series.":[28,94,105,126],"For":[29],"example,":[30,63],"behavior":[32,71],"drivers":[34],"can":[35,64,156],"be":[36,65,157],"captured":[37],"by":[38],"GPS":[39],"or":[40],"accelerometer":[41],"series":[45,60,133,150,155,210],"speeds,":[47],"directions,":[48],"accelerations.":[50],"We":[51,163,202],"propose":[52,79,164],"framework":[54,190],"for":[55,62,67],"outlier":[56],"detection":[57],"in":[58],"that,":[61],"used":[66],"identifying":[68,200],"dangerous":[69],"driving":[70],"hazardous":[73],"road":[74],"locations.":[75],"Specifically,":[76],"first":[78],"method":[81],"that":[82,183,225],"generates":[83],"statistical":[84],"features":[85,121],"enrich":[87],"feature":[89,116],"space":[90],"raw":[92],"Next,":[95],"utilize":[97],"an":[98],"autoencoder":[99,107],"reconstruct":[101],"enriched":[103,124,148],"The":[106],"performs":[108],"dimensionality":[109],"reduction":[110],"capture,":[112],"using":[113],"small":[115],"space,":[117],"most":[119],"representative":[120,136],"As":[127],"result,":[129],"reconstructed":[131,153],"only":[134],"capture":[135],"features,":[137],"whereas":[138],"outliers":[139],"often":[140],"have":[141],"non-representative":[142],"features.":[143],"Therefore,":[144],"deviations":[145],"from":[151],"taken":[158],"indicators":[160],"outliers.":[162,201,231],"study":[166],"autoencoders":[167],"based":[168],"on":[169,204],"convolutional":[170],"neural":[171,177],"networks":[172],"long-short":[174],"term":[175],"memory":[176],"networks.":[178],"In":[179],"addition,":[180],"show":[182],"embedding":[184],"contextual":[186],"information":[187],"into":[188,216],"has":[191],"potential":[193],"further":[195],"improve":[196],"accuracy":[198],"report":[203],"empirical":[205],"studies":[206],"with":[207],"multiple":[208],"data":[211],"sets,":[212],"which":[213],"offers":[214],"insight":[215],"design":[218],"properties":[219],"proposed":[222],"framework,":[223],"indicating":[224],"it":[226],"is":[227],"effective":[228],"at":[229],"detecting":[230]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":33},{"year":2022,"cited_by_count":33},{"year":2021,"cited_by_count":34},{"year":2020,"cited_by_count":28},{"year":2019,"cited_by_count":18},{"year":2018,"cited_by_count":5}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
